[索引]引用Balancing bike sharing systems with constraint programming的文章

1. LTI Branch-and-Price-and-Cut for the Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load☀️

• 异构车队和多站点静态自行车分流平衡问题的LTI分支和价格与削减
  FN Clarivate Analytics Web of Science
  AU Ding, Y; Zhang, JT; Sun, JQ
  AF Ding, Ye; Zhang, Jiantong;Sun, Jiaqing
• PY 2022

摘要:Heterogeneous Fleet and Multi-Depot Static Bike Rebalancing Problem with Split Load (HFMDSBRP-SD) is an extension of the Static Bike Rebalancing Problem, considering heterogeneous fleet multiple depots, allowing split load. It consists of finding a set of least-cost repositioning vehicle routes and determining each station’s pickup or delivery quantity to satisfy the demand of each station. We develop a branch-and-price-and-cut (BPC) where a tabu search column generator and a heuristic label-setting algorithm are introduced to accelerate the column generation procedure, the subset-row (SR) inequalities, the strong minimum number of vehicles (SMV) inequalities, and the enhanced elementary inequalities are extended fitting this problem and applied to speed up the global convergence rate. Computational results demonstrate the effectiveness of the BPC algorithm. Among 360 instances with a maximum size of 30, there are 298 instances capable of achieving optimality within two hour time limitation.

异构车队和多站点静态自行车重新平衡问题（HFMDSBRP-SD）是静态自行车重新均衡问题的扩展，考虑到异构车队多站点，允许拆分负载。它包括找到一组成本最低的重新定位车辆路线，并确定每个站点的取货或交货数量，以满足每个站点的需求。我们开发了一种分支和价格切割（BPC），其中引入了禁忌搜索列生成器和启发式标签设置算法，并将增强的初等不等式推广到该问题中，以提高全局收敛速度。计算结果证明了BPC算法的有效性。在最大大小为30的360个实例中，有298个实例能够在两小时的时间限制内实现最优。

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2. PROPOSING A MATHEMATICAL MODEL OF BALANCING THE INVENTORY OF MULTI-ZONE BICYCLE SHARING SYSTEMS WITH MOBILE STATIONS AND APPLYING MAINTENANCE CONSTRAINTS

• 提出了一种基于移动站的多区域自行车共享系统库存平衡的数学模型，并应用了维护约束
  AU Kaveh, F ;Shirouyehzad, H; Zolfani, SH; Arabzad, SM
  AF Kaveh, Farshad; Shirouyehzad, Hadi; Zolfani, Sarfaraz Hashemkhani ; Arabzad, S. Mohammad
• PY 2022

Regarding the necessity of developing transportation infrastructures and its increasing importance in urban issues, nowadays in different cities, bicycles are considered the main and sustainable vehicle along with walking and drawing more attention day by day. The case considers highly paramount since preservation of the environment, natural resources, and energy is one of the significant pillars of sustainable development, and urban transportation intensively influences it. Thus, Bicycle Sharing System (BSS) is recognized as an innovative urban transportation option that meets the citizens??? demand for commuting during the day. The BSS can highly affect the level of citizens??? health, and it can be counted as one of the leading health programs whether it???s added to the public transportation system, it can help the culture to be created to use bicycles instead of cars in most of the internal trips, and also it can be so influential in decreasing the air pollution and in the following its harmful effects on health issues. The mathematical model of rebalancing multi-zone BSS with mobile stations and applying maintenance constraints in a static status is considered in this research. The objective function of this research is a single-objective one, which is modeled with the aims of reducing the costs of traveled distances by the tracks within and outside the zones, reducing the costs of intact and defective bicycles transportation within and outside the zones, and eventually, reducing the costs of surplus bicycles depot at the stations. This issue is a multi-product one that includes different types of bicycles and balancing tracks. Computational results confirm the model???s efficiency. Also, sensitivity analysis has been done to prove that the model is affected by both parameters of storage costs of surplus bicycles and transportation costs within and outside the zones.

关于发展交通基础设施的必要性及其在城市问题中的日益重要性，如今在不同的城市，自行车被认为是主要和可持续的交通工具，与步行一起日益受到关注。该案例被认为是非常重要的，因为保护环境、自然资源和能源是可持续发展的重要支柱之一，而城市交通对其产生了强烈影响。因此，自行车共享系统（BSS）被公认为一种满足市民需求的创新城市交通方案？？？白天通勤需求。BSS可以高度影响公民的水平？？？健康，它可以算是领先的健康项目之一，无论是？？？它被添加到公共交通系统中，有助于创造在大多数内部旅行中使用自行车而不是汽车的文化，而且它可以在减少空气污染以及随之而来的对健康问题的有害影响方面发挥巨大的作用。本研究考虑了在静态状态下利用移动站重新平衡多区域BSS并应用维护约束的数学模型。本研究的目标函数是一个单一的目标函数，其建模目的是降低区域内外轨道的行驶距离成本，降低区域内外完整和有缺陷的自行车运输成本，最终降低站点多余自行车停车场的成本。这是一个多产品的问题，包括不同类型的自行车和平衡轨道。计算结果证实了模型？？？s效率。此外，还进行了敏感性分析，以证明该模型受到剩余自行车存储成本和区域内外运输成本两个参数的影响。

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3. Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike

Sharing Systems

• 在自行车共享系统中使用载具和自行车拖车重新定位自行车
  AU Zheng, XH; Tang, M; Liu, YC;Xian, ZZ;Zhuo, HHK
  AF Zheng, Xinghua;Tang, Ming; Liu, Yuechang; Xian, Zhengzheng ;Zhuo, Hankz Hankui
• PY 2021

Bike sharing systems (BSSs) are widely adopted in major cities of the world due to traffic congestion and carbon emissions. Although there have been approaches to exploit either bike trailers via crowdsourcing or carrier vehicles to reposition bikes in the “right” stations in the “right” time, they did not jointly consider the usage of both bike trailers and carrier vehicles. In this paper, we aim to take advantage of both bike trailers and carrier vehicles to reduce the loss of demand by determining whether bike trailers or carrier vehicles (or both) should be used. In addition, we also would like to maximize the overall profit with regard to the crowdsourcing of bike trailers and the fuel cost of carrier vehicles. In the experiment, we exhibit that our approach outperforms baselines in multiple data sets from bike sharing companies.
由于交通拥堵和碳排放，自行车共享系统（BSS）在世界主要城市被广泛采用。尽管已经有方法通过众包或运输车利用自行车拖车在“正确”的时间内将自行车重新定位到“正确”站点，但他们没有共同考虑自行车拖车和运输车的使用。在本文中，我们的目标是通过确定是否应使用自行车拖车或运输车（或两者）来利用自行车拖车和运输车，以减少需求损失。此外，我们还希望在自行车拖车的众包和运载车辆的燃料成本方面实现整体利润最大化。在实验中，我们展示了我们的方法在共享单车公司的多个数据集上优于基线。

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4 Measures of balance in combinatorial optimization

• 组合优化中的平衡度量
  AU Olivier, P ; Lodi, A; Pesant, G
  AF Olivier, Philippe; Lodi, Andrea ;Pesant, Gilles
• PY 2022

The concept of balance plays an important role in many combinatorial optimization problems. Yet there exist various ways of expressing balance, and it is not always obvious how best to achieve it. In this methodology-focused paper, we study three cases where its integration is deficient and analyze the causes of these inadequacies. We examine the characteristics and performance of the measures of balance used in these cases, and provide general guidelines regarding the choice of a measure.
平衡的概念在许多组合优化问题中起着重要作用。然而，表达平衡的方式多种多样，如何最好地实现平衡并不总是显而易见的。在这篇以方法论为重点的论文中，我们研究了三个其整合不足的案例，并分析了这些不足的原因。我们研究了在这些情况下使用的平衡措施的特点和性能，并提供了有关措施选择的一般指南。

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5. An enhanced artificial bee colony algorithm for the green bike repositioning problem with broken bikes⭐️

• 一种改进的人工蜂群算法求解自行车破损的绿色自行车重新定位问题
• AU Wang, Y ;Szeto, WY
  AF Wang, Yue; Szeto, W. Y.(⭐️)
• 期刊: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• PY 2021

The Bike Repositioning Problem (BRP) has raised many researchers? attention in recent years to improve the service quality of Bike Sharing Systems (BSSs). It is mainly about designing the routes and loading instructions for the vehicles to transfer bikes among stations in order to achieve a desirable state. This study tackles a static green BRP that aims to minimize the CO2 emissions of the repositioning vehicle besides achieving the target inventory level at stations as much as possible within the time budget. Two types of bikes are considered, including usable and broken bikes. The Enhanced Artificial Bee Colony (EABC) algorithm is adopted to generate the vehicle route. Two methods, namely heuristic and exact methods, are proposed and incorporated into the EABC algorithm to compute the loading/unloading quantities at each stop. Computational experiments were conducted on the real-world instances having 10?300 stations. The results indicate that the proposed solution methodology that relies on the heuristic loading method can provide optimal solutions for small instances. For large-scale instances, it can produce better feasible solutions than two benchmark methodologies in the literature.
自行车重新定位问题（BRP）引起了许多研究人员的关注？近年来，人们关注提高自行车共享系统（BSS）的服务质量。它主要是为车辆设计路线和装载指令，以便在站点之间转移自行车，以实现理想状态。本研究涉及一个静态绿色BRP，其目的是除了在时间预算内尽可能实现站点的目标库存水平之外，还将重新定位车辆的CO2排放降至最低。考虑两种类型的自行车，包括可用自行车和坏自行车。采用增强型人工蜂群（EABC）算法生成车辆路径。提出了两种方法，即启发式和精确方法，并将其结合到EABC算法中，以计算每个站点的装载/卸载量。在具有10？300个站点。结果表明，所提出的基于启发式加载方法的求解方法可以为小实例提供最优解。对于大规模实例，它可以产生比文献中的两种基准方法更好的可行解决方案。

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6. Modelling of User Behaviour for Static Rebalancing of Bike Sharing System: Transfer of Demand from Bike-Shortage Stations to Neighbouring Stations☀️

• 自行车共享系统静态再平衡的用户行为模型：需求从自行车短缺站转移到邻近站
• AU Affonso, RC ;Couffin, F ;Leclaire, P
  AF Costa Affonso, Roberta ;Couffin, Florent ;Leclaire, Patrice
• JOURNAL OF ADVANCED TRANSPORTATION
• PY 2021

Bike sharing systems are becoming more and more common around the world. One of the main difficulties is to ensure the availability of bicycles in order to satisfy users. To achieve this objective, managers of these systems set up rebalancing vehicles that displace bicycles to stations that are likely to be in a situation of bike shortage. In order to determine which stations must be supplied on a priority basis and the number of bicycles to be supplied (named in this paper as rebalancing plan), the aim is generally to reduce the lost demand for each station, i.e., the gap between the demand for bicycles and the number of bicycles at a station. On the one hand, this paper proposes an algorithm that evaluates the lost demand in a more realistic way, by describing the behaviour of users faced with a bike-shortage station. It takes into account the possibility that a proportion of users who cannot find bicycles will move to a neighbouring station that is not empty. This proportion depends on the distance between stations and corresponds to the number of users willing to walk a given distance to a neighbouring station. On the other hand, this algorithm provides the value of the objective function to be minimized to a static rebalancing plan algorithm based on a Random Search metaheuristic. The quantities of bicycles to be picked up and dropped off at each station are calculated in a static rebalancing context. The calculation of lost demand based on this algorithm, which simulates user behaviour, was compared with that one obtained by the classical method on a real numerical example obtained from the open data of Parisian Velib (more than 1200 stations). In addition, the efficiency of the rebalancing algorithm coupled with the user behaviour simulation algorithm was evaluated on this numerical example and allowed to obtain very good results compared to the rebalancing performed by the system operator.
自行车共享系统在世界各地越来越普遍。主要困难之一是确保自行车的可用性，以满足用户的需求。为了实现这一目标，这些系统的管理者建立了再平衡车辆，将自行车转移到可能处于自行车短缺状况的站点。为了确定哪些站点必须优先供应以及要供应的自行车数量（本文中称为再平衡计划），目的通常是减少每个站点的损失需求，即自行车需求与站点自行车数量之间的差距。一方面，本文提出了一种算法，通过描述面临自行车短缺站的用户的行为，以更现实的方式评估损失的需求。它考虑到了一部分找不到自行车的用户可能会搬到附近的非空站。该比例取决于站点之间的距离，并对应于愿意步行给定距离到达相邻站点的用户数量。另一方面，该算法将目标函数的值最小化为基于随机搜索元启发式的静态再平衡计划算法。每个站点上下车的自行车数量是在静态再平衡环境中计算的。基于该算法（模拟用户行为）的需求损失计算与经典方法计算的需求损失进行了比较，该方法基于从巴黎Velib（1200多个站点）的开放数据中获得的真实数值示例。此外，在该数值示例上评估了再平衡算法与用户行为模拟算法的效率，并且与系统操作员执行的再平衡相比，允许获得非常好的结果。

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7. Extending and Solving the Refrigerated Routing Problem

• 冷藏路径问题的扩展与解决
• AU Ceschia, S ; Di Gaspero, L; Meneghetti, A
  AF Ceschia, Sara ;Di Gaspero, Luca ;Meneghetti, Antonella
• ENERGIES
• PY 2020

近年来，冷链食品的增长令人印象深刻，这主要是由于顾客生活方式的改变。因此，冷藏食品的运输正成为链条的一个关键方面，旨在确保过程的效率和可持续性，同时保持高水平的产品质量。最近定义的冷藏路线问题（RRP）包括找到最佳的运输路线，以最小化牵引和冷藏部件的燃油消耗。总油耗与行驶距离、车辆负载和速度以及室外温度有着复杂的关系。所有这些因素反过来又取决于运输地区的交通和气候条件，这些因素在白天和一年中都会发生变化。最初的RRP已被扩展，以考虑到总驾驶成本，并增加了通过允许任意长的等待时间来降低交付速度的可能性，当这对目标功能有利时。新的RRP被表述和求解为混合整数规划和新的约束规划模型。此外，还提出了基于不同邻域结构组合的局部搜索元启发式技术（即延迟接受爬山）。比较和讨论了在一组基准情景下通过不同的解决方法获得的结果。

用处不大,所以没有记录英文摘要

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8.An Improved Iterated Local Search Algorithm for the Static Partial Repositioning Problem in Bike-Sharing System

• 自行车共享系统静态部分重新定位问题的改进迭代局部搜索算法
• AU Tang, Q ;Fu, Z ; Zhang, DZ ; Qiu, M; Li, MY
  AF Tang, Qiong ; Fu, Zhu ; Zhang, Dezhi ;Qiu, Meng ;Li, Minyi
• JOURNAL OF ADVANCED TRANSPORTATION
• PY 2020

In this paper, a single-vehicle static partial repositioning problem (SPRP) is investigated, which distinguishes the user dissatisfaction generated by different stations. The overall objective of the SPRP is to minimize the weighted sum of the total operational time and the total absolute deviation from the target number of bikes at all stations. An iterated local search is developed to solve this problem. A novel loading and unloading quantity adjustment operator is proposed to further improve the quality of the solution. Experiments are conducted on a set of instances from 30 to 300 stations to demonstrate the effectiveness of the proposed customized solution algorithm as well as the adjustment operator. Using a small example, this paper also reveals that the unit penalty cost has an effect on the repositioning strategies.
本文研究了一个单车静态部分重新定位问题（SPRP），该问题区分了不同站点产生的用户不满。SPRP的总体目标是最大限度地减少总运行时间和与所有站点自行车目标数量的总绝对偏差的加权和。为了解决这个问题，开发了迭代局部搜索。提出了一种新的加载和卸载量调整算子，以进一步提高解决方案的质量。在30到300个站点的一组实例上进行了实验，以证明所提出的定制解决方案算法以及调整算子的有效性。通过一个小例子，本文还揭示了单位惩罚成本对重新定位策略的影响。

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9.Station-Free Bike Rebalancing Analysis: Scale, Modeling, and Computational Challenges

• Station Free Bike再平衡分析：规模、建模和计算挑战
• AU Jin, XT; Tong, DQ
  AF Jin, Xueting ;Tong, Daoqin
• ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
• PY 2020

In the past few years, station-free bike sharing systems (SFBSSs) have been adopted in many cities worldwide. Different from conventional station-based bike sharing systems (SBBSSs) that rely upon fixed bike stations, SFBSSs allow users the flexibility to locate a bike nearby and park it at any appropriate site after use. With no fixed bike stations, the spatial extent/scale used to evaluate bike shortage/surplus in an SFBSS has been rather arbitrary in existing studies. On the one hand, a balanced status using large areas may contain multiple local bike shortage/surplus sites, leading to a less effective rebalancing design. On the other hand, an imbalance evaluation conducted in small areas may not be meaningful or necessary, while significantly increasing the computational complexity. In this study, we examine the impacts of analysis scale on the SFBSS imbalance evaluation and the associated rebalancing design. In particular, we develop a spatial optimization model to strategically optimize bike rebalancing in an SFBSS. We also propose a region decomposition method to solve large-sized bike rebalancing problems that are constructed based on fine analysis scales. We apply the approach to study the SFBSS in downtown Beijing. The empirical study shows that imbalance evaluation results and optimal rebalancing design can vary substantially with analysis scale. According to the optimal rebalancing results, bike repositioning tends to take place among neighboring areas. Based on the empirical study, we would recommend 800 m and 100/200 m as the suitable scale for designing operator-based and user-based rebalancing plans, respectively. Computational results show that the region decomposition method can be used to solve problems that cannot be handled by existing commercial optimization software. This study provides important insights into effective bike-share rebalancing strategies and urban bike transportation planning.
在过去几年中，全球许多城市都采用了无站共享单车系统（SFBSS）。与依赖固定自行车站点的传统基于站点的自行车共享系统（SBBSS）不同，SFBSS允许用户灵活地在附近定位自行车，并在使用后将其停放在任何合适的地点。由于没有固定的自行车站，在现有研究中，用于评估SFBSS中自行车短缺/过剩的空间范围/尺度相当随意。一方面，使用大面积的平衡状态可能包含多个本地自行车短缺/过剩站点，从而导致不太有效的再平衡设计。另一方面，在小范围内进行不平衡评估可能没有意义或必要，同时显著增加了计算复杂性。在本研究中，我们考察了分析规模对SFBSS失衡评估和相关再平衡设计的影响。特别是，我们开发了一个空间优化模型，以战略性地优化SFBSS中的自行车再平衡。我们还提出了一种区域分解方法来解决基于精细分析尺度构建的大型自行车再平衡问题。我们将该方法应用于北京市中心的SFBSS研究。实证研究表明，不平衡评估结果和最优再平衡设计会随着分析规模的变化而发生很大变化。根据最佳再平衡结果，自行车的重新定位往往发生在相邻地区。根据实证研究，我们将分别推荐800m和100/200m作为设计基于运营商和用户的再平衡计划的合适尺度。计算结果表明，区域分解方法可用于解决现有商业优化软件无法处理的问题。这项研究为有效的自行车共享再平衡策略和城市自行车交通规划提供了重要见解。

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10.A static bike repositioning model in a hub-and-spoke network framework

• 轮毂轮辐网络框架中的静态自行车重新定位模型
• AU Huang, D ;Chen, XY; Liu, ZY; Lyu, C; Wang, SA; Chen, XW
  AF Huang, Di ; Chen, Xinyuan; Liu, Zhiyuan; Lyu, Cheng; Wang, Shuaian ; Chen, Xuewu
• TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
• PY 2020

This paper addresses a static bike repositioning problem by embedding a short-term demand forecasting process, the Random Forest (RF) model, to account for the demand dynamics in the daytime. To tackle the heterogeneous repositioning fleets, a novel repositioning operation strategy constructed on the hub-and-spoke network framework is proposed. The repositioning optimization model is formulated using mixed-integer programming. An artificial bee colony algorithm, integrated with a commercial solver, is applied to address computational complexity. Experimental results show that the RF can achieve a high forecasting accuracy, and the proposed repositioning strategy can efficiently decrease the users’ dissatisfaction.
本文通过嵌入短期需求预测过程（随机森林（RF）模型）来解决静态自行车重新定位问题，以说明白天的需求动态。为了解决异构的重新定位车队，提出了一种基于轮辐网络框架的新的重新定位运营策略。采用混合整数规划建立了重新定位优化模型。将人工蜂群算法与商业求解器相结合，用于解决计算复杂性问题。实验结果表明，该方法可以获得较高的预测精度，所提出的重新定位策略可以有效地减少用户的不满。

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11. A review of bicycle-sharing service planning problems

• 自行车共享服务规划问题综述
• AU Shui, CS ;Szeto, WY;
  AF Shui, C. S; Szeto, W. Y.⭐️
• TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• PY 2020

This paper reviews and systematically classifies the existing literature of bicycle-sharing service planning problems (BSPPs) at strategic, tactical, and operational decision levels with the reference to the novel bicycle sharing service planning process introduced herein. The current research gaps are identified and discussed. The future research directions of the three decision level problems are proposed according to four main categories, namely new diversity, realism, integrality, and technology. This review also points out important future research directions for multi-level BSPPs and the integration of bicycle sharing systems with existing multi-modal transportation systems.
本文参考本文介绍的新型自行车共享服务规划过程，在战略、战术和运营决策层面对现有的自行车共享服务计划问题（BSPP）文献进行了回顾和系统分类。确定并讨论了当前的研究差距。根据新多样性、现实性、完整性和技术性四个主要类别，提出了三个决策层问题的未来研究方向。该综述还指出了多层次BSPP以及自行车共享系统与现有多模式交通系统集成的重要未来研究方向。

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12. A multicommodity unpaired pickup and delivery vehicle routing problem with split loads and unloads

• 一个多商品非配对装卸车辆路径问题
• AU Xu, DY；Li, KP； Yang, JH； Cui, LG
  AF Dongyang, Xu；Kunpeng, Li；Jiehui, Yang； Ligang, Cui
• INDUSTRIAL MANAGEMENT & DATA SYSTEMS

Purpose This paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs. Design/methodology/approach A mixed integer programming (MIP) model is built and five types of valid inequalities for tightening the solution space are derived. An improved variable neighborhood search (IVNS) algorithm is presented combining the developed multistart initial solution strategy and modified neighborhood local search procedure. Findings Experimental results demonstrate that: with less decision variables considered, the proposed model can solve more instances compared to the existing model in previous literature. The valid inequalities utilized to tighten the searching space can efficiently help the model to obtain optimal solutions or high-quality lower bounds. The improved algorithm is efficient to obtain optimal or near-optimal solutions and superior to the compared algorithm in terms of solution quality, computational time and robustness. ractical implications This research not only can help reduce operational costs and improve logistics efficiency for relevant enterprises, but also can provide guidance for constructing the decision support system of logistics intelligent scheduling platform to cater for centralized management and control. Originality/value This paper develops a more compact model and some stronger valid inequalities. Moreover, the proposed algorithm is easy to implement and performs well.

目的本文旨在探讨在生产/销售企业中常见的客户之间的商品转运计划，以节省运营成本。设计/方法/方法建立了一个混合整数规划（MIP）模型，并导出了用于收紧解空间的五种有效不等式。结合改进的多阶段初始解策略和改进的邻域局部搜索过程，提出了一种改进的可变邻域搜索（IVNS）算法。实验结果表明：与先前文献中的现有模型相比，在考虑较少决策变量的情况下，所提出的模型可以解决更多的实例。用于压缩搜索空间的有效不等式可以有效地帮助模型获得最优解或高质量下界。改进算法能够有效地获得最优或近似最优解，并且在解质量、计算时间和鲁棒性方面优于比较算法。本研究不仅可以帮助相关企业降低运营成本，提高物流效率，而且可以为构建适应集中管理和控制的物流智能调度平台决策支持系统提供指导。原创/价值本文开发了一个更紧凑的模型和一些更强的有效不等式。此外，该算法易于实现，性能良好。

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13.TI Addressing the Bike Repositioning Problem in Bike Sharing System: A

Two-Stage Stochastic Programming Model

• 解决自行车共享系统中的自行车重定位问题 两阶段随机规划模型
• AU Tang, Q； Fu, Z； Zhang, DZ； Guo, H； Li, MY
  AF Tang, Qiong; Fu, Zhuo;Zhang, Dezhi;Guo, Hao; Li, Minyi
• SO SCIENTIFIC PROGRAMMING
• PY 2020

AB In this paper, a bike repositioning problem with stochastic demand is studied. The problem is formulated as a two-stage stochastic programming model to optimize the routing and loading/unloading decisions of the repositioning truck at each station and depot under stochastic demands. The goal of the model is to minimize the expected total sum of the transportation costs, the expected penalty costs at all stations, and the holding cost of the depot. A simulated annealing algorithm is developed to solve the model. Numerical experiments are conducted on a set of instances from 20 to 90 stations to demonstrate the effectiveness of the solution algorithm and the accuracy of the proposed two-stage stochastic model.

本文研究了随机需求下的自行车重新定位问题。该问题被描述为一个两阶段随机规划模型，以优化随机需求下每个车站和仓库的重新定位卡车的路径选择和装卸决策。该模型的目标是最小化运输成本、所有车站的期望惩罚成本和仓库的持有成本的期望总和。提出了一种模拟退火算法来求解该模型。通过对20-90个站点的数值实验，验证了求解算法的有效性和两阶段随机模型的准确性。

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14.TI A Bike-sharing Optimization Framework Combining Dynamic Rebalancing and User Incentives

• 结合动态再平衡和用户激励的自行车共享优化框架
• AU Chiariotti, F;Pielli, C;Zanella, A; Zorzi, M
  AF Chiariotti, Federico;Pielli, Chiara;Zanella, Andrea;Zorzi, Michele
• SO ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS
• PY 2020

AB Bike-sharing systems have become an established reality in cities all across theworld and are a key component of the Smart City paradigm. However, the unbalanced traffic patterns during rush hours can completely empty some stations, while filling others, and the service becomes unavailable for further users. The traditional approach to solve this problem is to use rebalancing trucks, which take bikes from full stations and deposit them at empty ones, reducing the likelihood of system outages. Another paradigm that is gaining steam is gamification, i.e., incentivizing users to fix the system by influencing their behavior with rewards and prizes. In this work, we combine the two efforts and show that a joint optimization considering both rebalancing and incentives results in a higher service quality for a lower cost than using simple rebalancing. We use simulations based on the New York CitiBike usage data to validate our model and analyze several schemes to optimize the bike-sharing system.

共享单车系统已成为世界各地城市的既定现实，是智慧城市模式的关键组成部分。然而，高峰时段不平衡的交通模式可能会完全清空一些车站，而填满其他车站，这项服务对更多的用户来说变得不可用。解决这一问题的传统方法是使用再平衡卡车，将自行车从满站取下并存放在空站，从而降低系统中断的可能性。另一个正在兴起的范式是游戏化，即通过奖励和奖品影响用户的行为来激励用户修复系统。在这项工作中，我们结合了这两种努力，并表明，与使用简单的再平衡相比，考虑再平衡和激励的联合优化可以以更低的成本获得更高的服务质量。我们使用基于纽约CitiBike使用数据的模拟来验证我们的模型，并分析优化共享单车系统的几个方案。

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15.TI Generating efficient rebalancing routes for bikeshare programs using a

genetic algorithm

• 使用为自行车共享计划生成高效的重新平衡路线 遗传算法
• AU Kroes, JR; Manikas, AS; Gattiker, TF
  AF Kroes, James R.; Manikas, Andrew S.; Gattiker, Thomas F.
• SO JOURNAL OF CLEANER PRODUCTION
• PY 2020

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16. Study on Bike Sharing Rebalancing: Evidence from Kunming

• 自行车共享再平衡研究:来自昆明的证据

• AU Yin, AT; Ning, BJ; Wang, YQ
  AF Yin, Anteng;Ning, Bojin;Wang, Yeqin

• SO RESILIENCE AND SUSTAINABLE TRANSPORTATION SYSTEMS: PROCEEDINGS OF THE

• PY 2020

AB Lots of cities have developed a bike sharing system, but how to deploy a bike sharing system reasonably is urgent issue in the cities like Kunming. A knowledge based on these factors that rebalancing on a bike sharing system will work on to support cities to design an efficient service bike sharing system while decreasing re-balancing costs. We collect traffic-zone-level bike sharing usage data in Kunming, analyze the bike sharing time-variation and daily variation characteristics of arrivals and departures. Especially, we built multiple regression model to quantify effect of socio-demographic characteristics and land-use characteristics on time-variation and daily variation characteristics of arrivals and departures. We then define the absolute value of arrivals minus departures as balance index, and develop a binary logit model to estimate the influence of socio-demographic characteristics, land-use characteristics, and public transit characteristics on re-balancing. The results provide a basis for the re-balancing of a bike sharing system.
BN 978-0-7844-8290-2
许多城市已经开发了共享单车系统，但如何合理地部署共享单车系统是昆明等城市迫切需要解决的问题。基于这些因素的知识，重新平衡共享单车系统将有助于支持城市设计高效的服务共享单车系统，同时降低重新平衡成本。我们收集了昆明市交通区级别的共享单车使用数据，分析了共享单车到达和离开的时间变化和每日变化特征。特别是，我们建立了多元回归模型，以量化社会人口特征和土地利用特征对到达和离开的时间变化和日变化特征的影响。然后，我们将到达量减去离开量的绝对值定义为平衡指数，并开发了一个二元逻辑模型，以估计社会人口特征、土地利用特征和公共交通特征对重新平衡的影响。结果为共享单车系统的重新平衡提供了基础。
邮编978-0-7844-8290-2

17.TI Social media analytics to connect system performability and quality of

experience, with an application to Citibike

• TI社交媒体分析将系统可执行性和质量联系起来 经验，申请Citibik
• AU Svartzman, GG;Ramirez-Marquez, JE;Barker, K
  AF Svartzman, Gabriela Gongora;Ramirez-Marquez, Jose E.;Barker, Kash
• SO COMPUTERS & INDUSTRIAL ENGINEERING
• PY 2020

AB Historically performance of city services has mostly been evaluated from a performability perspective based on what is commonly understood as a quality of service (QoS) analysis. High values of QoS are generally perceived by systems owners as reflective of a high quality of experience (QoE) by the system users. Unfortunately, such a statement is many times untrue. There is a lack of connection between the user experience and the system performance. As such, and given the availability of social media data regarding the usage of services and experiences, this work presents a novel framework to bring together QoS and QoE analyses, to integrate performance metrics with user expectations of services. This framework is illustrated via the bicycle sharing program of New York City, Citibike, where the combination of both QoS and QoE provides insights into a variety of issues related to the city and the service itself.

从历史上看，城市服务的性能大多是从可执行性的角度进行评估的，其基础是通常所理解的服务质量(QoS)分析。系统所有者通常认为高QoS值反映了系统用户的高体验质量(QoE)。不幸的是，这种说法很多时候是不真实的。用户体验和系统性能之间缺乏联系。因此，考虑到有关服务使用和体验的社交媒体数据的可用性，这项工作提出了一个新的框架，将QoS和QoE分析结合起来，将性能指标与用户对服务的期望相结合。这一框架通过纽约市的自行车共享计划Citibike进行了说明，其中QoS和QoE的结合为与城市和服务本身相关的各种问题提供了见解

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18.TI Modelling Methods for Planning and Operation of Bike-Sharing Systems

• 自行车共享系统规划和运行的建模方法
• AU Nath, RB;Rambha, T
  AF Nath, Rito Brata; Rambha, Tarun
• SO JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE
• PY 2019

AB Bike-sharing systems (BSSs) are emerging as a popular type of shared vehicle platform where users can rent bicycles without having to own and maintain them. BSSs are ideal for short trips and for connecting to public transit systems. Bicycle usage is associated with several unique characteristics which make planning and operation of BSSs very different from car sharing problems and other traditional transportation modelling approaches. In this paper, we summarize existing literature on strategic planning which involves selecting stations, designing bike paths, and figuring out station capacity. Research on operational measures which include day-to-day and within-day repositioning activities are also collated. Additionally, models for understanding demand, pricing and incentives, maintenance, and other technological aspects are reviewed.

行车共享系统(BSSs)正在成为一种流行的共享车辆平台，用户可以租用自行车，而不必拥有和维护它们。BSS是短途旅行和连接公共交通系统的理想选择。自行车的使用与几个独特的特征相关联，这些特征使得BSS的规划和运行与汽车共享问题和其他传统的交通建模方法非常不同。在本文中，我们总结了战略规划的现有文献，涉及选择站，设计自行车道，并计算出站的能力。还整理了关于运营措施的研究，包括日常和日内重新定位活动。此外，还回顾了理解需求、定价和激励、维护和其他技术方面的模型

—###19.TI Modelling Methods for Planning and Operation of Bike-Sharing Systems

• 自行车共享系统规划和运行的建模方法
• AU Nath, RB;Rambha, T
  AF Nath, Rito Brata;Rambha, Tarun
• SO JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE
• PY2019

AB Bike-sharing systems (BSSs) are emerging as a popular type of shared vehicle platform where users can rent bicycles without having to own and maintain them. BSSs are ideal for short trips and for connecting to public transit systems. Bicycle usage is associated with several unique characteristics which make planning and operation of BSSs very different from car sharing problems and other traditional transportation modelling approaches. In this paper, we summarize existing literature on strategic planning which involves selecting stations, designing bike paths, and figuring out station capacity. Research on operational measures which include day-to-day and within-day repositioning activities are also collated. Additionally, models for understanding demand, pricing and incentives, maintenance, and other technological aspects are reviewed.
行车共享系统(BSSs)正在成为一种流行的共享车辆平台，用户可以租用自行车，而不必拥有和维护它们。BSS是短途旅行和连接公共交通系统的理想选择。自行车的使用与几个独特的特征相关联，这些特征使得BSS的规划和运行与汽车共享问题和其他传统的交通建模方法非常不同。在本文中，我们总结了战略规划的现有文献，涉及选择站，设计自行车道，并计算出站的能力。还整理了关于运营措施的研究，包括日常和日内重新定位活动。此外，还回顾了理解需求、定价和激励、维护和其他技术方面的

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20.TI Effect of built environment on shared bicycle reallocation: A case study on Nanjing, China

• 建成环境对共享单车再分配的影响——以南京市为例
• AU Zhao, D; Ong, GP; Wang, W;Hu, XJ
  AF Zhao, De; Ong, Ghim Ping; Wang, Wei;Hu, Xiao Jian
• SO TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
  *PY2019

AB Shared bicycles provide a convenient mobility option to commuters especially for short-distance trips. Nevertheless, it also presents a challenge to bicycle-sharing operators as they have to deal with reallocation issues, i.e. removing bicycles from parking facilities which are at or near capacity and refilling parking facilities that are in need of bicycles. Few studies in the literature have actually tried understanding why certain docking stations are prone to excessive demand or suffer from a lack of parking supply. This paper attempts to identify the demographic, built-environment and transport-infrastructure indicators that can potentially aid policy-makers and operators in identifying parking facilities prone to bicycle reallocation. In particular, we have adopted the bicycle sharing operations in Nanjing, China as a case study to understand how such indicators can be identified for appropriate parking infrastructural enhancements. To achieve this goal, this study has established zero-inflated negative binomial models using multi-source data including point-of-interest (POI), daily weather, transit stop location, demographic data and bike-share smart card data. The model results obtained from this study suggest that built environment correlates significantly to shared bicycle reallocation count. In general, bicycle docking stations with large reallocation counts are more likely to be found near residences, bus stops, metro stations, employment areas, restaurants, amenities, parks, sports facilities, and clinics/hospitals; while stations near entertainment facilities, places of attraction, hotels, shopping malls, and educational institution tend to have balanced demand and supply. Analysis on the elasticity values revealed that mean temperature and station capacity are the most influential factors in bicycle reallocation. Among all POIs, presence of restaurants and areas with high employment tend to exhibit strongly a need for morning bicycle removal and evening bicycle refilling at docked stations. Policy makers can provide actual guidelines in the planning of shared bicycle parking facilities using the findings and methodologies presented in this study.

共享单车为通勤者提供了便捷的出行选择，尤其是短途旅行。然而，这也给自行车共享运营商带来了挑战，因为他们必须处理重新分配问题，即从容量或接近容量的停车设施中移除自行车，并重新填充需要自行车的停车设施。文献中很少有研究试图了解为什么某些停靠站容易出现过度需求或停车供应不足的问题。本文试图确定人口统计、建筑环境和交通基础设施指标，这些指标可能有助于决策者和运营商确定容易重新分配自行车的停车设施。特别是，我们采用了中国南京的自行车共享运营作为案例研究，以了解如何确定此类指标，以适当改善停车基础设施。为了实现这一目标，本研究使用包括兴趣点（POI）、每日天气、公交站点位置、人口统计数据和自行车共享智能卡数据在内的多源数据建立了零膨胀负二项模型。从本研究中获得的模型结果表明，建筑环境与共享自行车重新分配数量显著相关。一般而言，在住宅、公交车站、地铁站、就业区、餐厅、便利设施、公园、体育设施和诊所/医院附近更容易发现重新分配数量较大的自行车停靠站；而靠近娱乐设施、景点、酒店、购物中心和教育机构的车站往往需求和供应平衡。对弹性值的分析表明，平均温度和站点容量是自行车重新分配的最影响因素。在所有POI中，餐馆和就业率高的地区往往强烈需要在停靠站拆除早晨的自行车和晚上的自行车。政策制定者可以使用本研究中提出的研究结果和方法，为共享自行车停车设施的规划提供实际指导。

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21.TI The Dynamic Bowser Routing Problem

• 动态布瑟路由问题
• AU Rossi, R; Tomasella, M; Martin-Barragan, B;Embley, T; Walsh, C; Langston, M
  AF Rossi, Roberto;Tomasella, Maurizio; Martin-Barragan, Belen; Embley, Tim; Walsh, Christopher; Langston, Matthew
• SO EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
• PY 2019

AB We investigate opportunities offered by telematics and analytics to enable better informed, and more integrated, collaborative management decisions across construction sites. We focus on efficient refuelling of assets across construction sites. More specifically, we develop decision support models that, by leveraging data supplied by different assets, schedule refuelling operations by minimising the distance travelled by the refuelling truck - the so-called “bowser” - as well as fuel shortages. Motivated by a practical case study elicited in the context of a project we recently conducted at Crossrail, we introduce the Dynamic Bowser Routing Problem. In this problem the decision maker aims to dynamically refuel, by dispatching a bowser truck, a set of assets which consume fuel and whose location changes over time; the goal is to ensure that assets do not run out of fuel and that the bowser covers the minimum possible distance. We investigate deterministic and stochastic variants of this problem and introduce effective and scalable mathematical programming models to tackle these cases. We demonstrate the effectiveness of our approaches in the context of an extensive computational study designed around data collected on site. © 2018 Elsevier B.V. All rights reserved.

我们调查远程信息处理和分析提供的机会，以便在建筑工地上做出更明智、更集成的协作管理决策。我们专注于建筑工地资产的高效加油。更具体地说，我们开发了决策支持模型，通过利用不同资产提供的数据，通过最小化加油车（所谓的“bowser”）行驶的距离以及燃料短缺来安排加油作业。受我们最近在Crossrail进行的一个项目的实际案例研究的启发，我们介绍了动态Bowser路由问题。在这个问题中，决策者的目标是通过调度一辆bowser卡车来动态地为一组消耗燃料且其位置随时间变化的资产加油；目标是确保资产不会耗尽燃料，并确保bowser覆盖尽可能短的距离。我们研究了这个问题的确定性和随机变量，并引入了有效和可扩展的数学规划模型来解决这些问题。我们在围绕现场收集的数据进行的广泛计算研究中证明了我们方法的有效性。（C） 2018爱思唯尔B.V.保留所有权利。

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22.TI Instance Generation via Generator Instances

• 通过生成器实例生成实例
• AU Akgun, O; Dang, N; Miguel, I;Salamon, AZ; Stone, C
  AF Akgun, Ozgur; Nguyen Dang; Miguel, Ian;Salamon, Andras Z.; Stone, Christopher
  BE Schiex, T;DeGivry, S
• SO PRINCIPLES AND PRACTICE OF CONSTRAINT
• PY 2019

AB Access to good benchmark instances is always desirable when developing new algorithms, new constraint models, or when comparing existing ones. Hand-written instances are of limited utility and are time-consuming to produce. A common method for generating instances is constructing special purpose programs for each class of problems. This can be better than manually producing instances, but developing such instance generators also has drawbacks. In this paper, we present a method for generating graded instances completely automatically starting from a class-level problem specification. A graded instance in our present setting is one which is neither too easy nor too difficult for a given solver. We start from an abstract problem specification written in the Essence language and provide a system to transform the problem specification, via automated type-specific rewriting rules, into a new abstract specification which we call a generator specification. The generator specification is itself parameterised by a number of integer parameters; these are used to characterise a certain region of the parameter space. The solutions of each such generator instance form valid problem instances. We use the parameter tuner irace to explore the space of possible generator parameters, aiming to find parameter values that yield graded instances. We perform an empirical evaluation of our system for five problem classes from CSPlib, demonstrating promising results.
OI Miguel, Ian/0000-0002-6930-2686; Salamon, Andras/0000-0002-1415-9712;
Dang, Nguyen/0000-0002-2693-6953; Akgun, Ozgur/0000-0001-9519-938X

在开发新算法、新约束模型或比较现有算法时，总是需要访问良好的基准实例。手写实例的实用性有限，制作耗时。生成实例的一种常见方法是为每类问题构造专用程序。这可能比手动生成实例更好，但开发这样的实例生成器也有缺点。在本文中，我们提出了一种从类级问题规范开始完全自动生成分级实例的方法。我们当前设置中的分级实例对于给定的解算器来说既不太容易也不太困难。我们从用Essence语言编写的抽象问题规范开始，并提供一个系统，通过自动类型特定的重写规则将问题规范转换为新的抽象规范，我们称之为生成器规范。发电机规格本身由多个整数参数参数化；这些用于表征参数空间的特定区域。每个这样的生成器实例的解决方案形成有效的问题实例。我们使用参数调谐器irace来探索可能的生成器参数空间，旨在找到生成分级实例的参数值。我们对CSPlib中的五个问题类进行了系统的实证评估，证明了有希望的结果。
OI Miguel，Ian/0000-0002-6930-2686；Salamon，Andras/0000-0002-1415-9712；
Dang，Nguyen/0000-0002-2693-6953；Akgun，Ozgur/0000-0001-9519-938X

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23.TI Aggregated Indicator for Assessing Station Criticality of Bike Sharing Systems

• 用于评估自行车共享系统站点重要性的综合指标
• AU Affonso, RC;Couffin, F
  AF Affonso, Roberta C.; Couffin, Florent
  BE Zheng, F; Chu, F;Liu, M
• SO PROCEEDINGS OF THE 2019 INTERNATIONAL
• PY 2019

AB Bike Sharing Systems (BSS) are implemented in numerous cities around the world. The users’ satisfaction is directly affected by the availability of bicycles and docking points at the stations. The assessment of users’ satisfaction is an important issue to enable the system manager to understand, manage and improve the service quality of the BSS. This paper proposes to define an aggregated performance indicator for BSS stations. This indicator allows to measure the station criticality by integrating the unavailability of bikes and dockings of this station, and also of the neighboring stations. The integration of neighboring stations will be defined according to the distance that users is willing to walk to reach them. This indicator is applied to a part of Velib’ system and will be analyzed in relation to a non-aggregated criticality indicator. The proposed aggregated criticality indicator can be implemented, for example, to define priority stations to be rebalanced by rebalancing operations. Open data, over a six weeks period, from JCDecaux (Velib’ operator) was used to implement this study.
自行车共享系统（BSS）在世界各地的许多城市实施。用户的满意度直接受到车站自行车和停靠点的可用性的影响。用户满意度评估是系统管理者了解、管理和改进BSS服务质量的重要问题。本文提出定义BSS站的聚合性能指标。该指标允许通过整合该站点以及相邻站点的自行车不可用性和停靠情况来衡量站点的关键性。相邻站点的整合将根据用户愿意步行到达的距离来定义。该指标适用于Velib系统的一部分，并将根据非聚合临界指标进行分析。例如，可以实施拟议的聚合临界度指标，以定义要通过再平衡操作进行再平衡的优先站点。JCDecaux（Velib的运营商）在六周内提供的开放数据用于实施本研究。

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24.TI DYNAMIC MATCHING OF UNCERTAIN DEMAND WITH

• 不确定需求的动态匹配
• AU Chou, YC; Kamano, K;Yu, MS
  AF Chou, Yon-Chun; Kamano, Katayut;Yu, Maio-Shan
• SO INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND
  PRACTICE
• PY 2019

AB Most production and inventory models address either demand or supply uncertainty. When both uncertainties are involved, intermediary inventory stock usually serves as a buffering mechanism so that they are dealt with separately. In this paper, we address a new problem of directly matching uncertain demand with uncertain supply that arises in the dynamic bike balancing problem of bike sharing systems. We show that it is not optimal for the bike stock in any station to be less than a certain floor threshold or more than a certain upper threshold when the dual performance measures of bike utilization and lost customers are considered. We next construct a threshold-based Integer Programming model for dynamic balancing. Through numerical examples, we find that the problem is characterized by many multiple optimal solutions, which lead to dispersed transfers of bikes, but this imperfection is resolved by ranking and re-sequencing candidate transfers in an enhancing step. By using random numerical cases, we compare the merits of the model with a mean-value model, and assess its capability of prepositioning bikes to hedge the uncertainty. This paper contributes to the methodology of matching uncertain demand with uncertain supply.

大多数生产和库存模型解决了需求或供应的不确定性。当这两种不确定性都涉及时，中间库存通常作为缓冲机制，以便单独处理。在本文中，我们解决了共享单车系统的动态自行车平衡问题中出现的一个新问题，即不确定需求与不确定供应的直接匹配。我们表明，当考虑自行车利用率和流失客户的双重性能指标时，任何站点的自行车库存低于某一楼层阈值或高于某一上限阈值都不是最优的。接下来，我们构建了一个基于阈值的动态平衡整数规划模型。通过数值示例，我们发现该问题的特点是有许多多个最优解，这导致自行车的分散转移，但通过在增强步骤中对候选转移进行排序和重新排序，解决了这一缺陷。通过使用随机数字案例，我们将该模型与均值模型的优点进行了比较，并评估了其预定位自行车以对冲不确定性的能力。本文有助于不确定需求与不确定供应的匹配方法。

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25.TI A Bilevel Programming Model and Algorithm for the Static Bike Repositioning Problem

*静态自行车重定位问题的双层规划模型及算法

• AU Tang, Q;Fu, Z;Qiu, M
  AF Tang, Qiong; Fu, Zhuo; Qiu, Meng
• SO JOURNAL OF ADVANCED TRANSPORTATION
• PY 2019

AB In this paper, by taking the outsourcing transportation mode into account, a bilevel programming model is proposed to formulate the static bike repositioning (SBR) problem, which can be used to determine the number of bikes loaded and unloaded at each station and the optimal truck routes in bike sharing systems (BSS). The upper-level BSS providers determine the optimal loading and unloading quantities at stations to minimize the total penalties. The lower-level truck owner pursues the minimum transportation route cost. An iterated local search and tabu search are developed to solve the model. Computational tests on a set of instances from 20 to 200 bikes demonstrate the effectiveness of the model and algorithms proposed, together with some insightful findings.

在考虑外包运输模式的基础上，提出了一个双层规划模型来描述静态单车重定位问题，该模型可用于确定单车共享系统中每个站点的单车装卸量和最优卡车路线。上层BSS提供商确定车站的最佳装载和卸载数量，以最小化总损失。下层货车车主追求运输路线成本最小。为求解该模型，提出了迭代局部搜索和禁忌搜索算法。对20到200辆自行车的一组实例的计算测试证明了所提出的模型和算法的有效性，以及一些有见地的发现。

–### 26.TI A Constraint Programming Approach to Electric Vehicle

• 电动汽车的约束规划方法
• AU Booth, KEC;Beck, JC
  AF Booth, Kyle E. C.;Beck, J. Christopher
  BE Rousseau, LM;Stergiou, K
• SO INTEGRATION OF CONSTRAINT PROGRAMMING,
  *PY 2019

AB The Electric Vehicle Routing Problem with Time Windows (EVRPTW) extends traditional vehicle routing to address the recent development of electric vehicles (EVs). In addition to traditional VRP problem components, the problem includes consideration of vehicle battery levels, limited vehicle range due to battery capacity, and the presence of vehicle recharging stations. The problem is related to others in emissions-conscious routing such as the Green Vehicle Routing Problem (GVRP). We propose the first constraint programming (CP) approaches for modeling and solving the EVRPTW and compare them to an existing mixed-integer linear program (MILP). Our initial CP model follows the alternative resource approach previously applied to routing problems, while our second CP model utilizes a single resource transformation. Experimental results on various objectives demonstrate the superiority of the single resource transformation over the alternative resource model, for all problem classes, and over MILP, for the majority of medium-to-large problem classes. We also present a hybrid MILP-CP approach that outperforms the other techniques for distance minimization problems over long scheduling horizons, a class that CP struggles with on its own.

带时间窗的电动车辆路径问题（EVRPTW）扩展了传统的车辆路径，以解决电动车辆（EV）的最新发展。除了传统的VRP问题组件外，该问题还包括考虑车辆电池电量、电池容量导致的车辆续航里程受限以及车辆充电站的存在。该问题与排放意识路线中的其他问题有关，如绿色车辆路线问题（GVRP）。我们提出了第一种用于EVRPTW建模和求解的约束规划（CP）方法，并将其与现有的混合整数线性规划（MILP）进行了比较。我们的初始CP模型遵循先前应用于路由问题的替代资源方法，而我们的第二个CP模型使用单个资源转换。不同目标的实验结果表明，对于所有问题类，单一资源转换优于替代资源模型，对于大多数中大型问题类，单个资源转换优于MILP。我们还提出了一种混合MILP-CP方法，该方法在长调度范围内的距离最小化问题上优于其他技术，这是CP自己难以解决的问题。

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27.TI Static green repositioning in bike sharing systems with broken bikes

• 自行车共享系统中自行车损坏时的静态绿色重新定位
• AU Wang, Y;Szeto, WY
  AF Wang, Yue; Szeto, W. Y.
• SO TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
• PY 2018

AB Bike-Sharing Systems (BSSs) and environmental concerns have been receiving increasing popularity in transportation operations. In BSSs, the distribution of bike demand often mismatches with bike supply and there are broken bikes. Usable bikes are needed to redistribute between stations to satisfy the demand and all broken bikes need to be carried back to the depot for repairs. Both types of bikes are often transported by fossil-fueled vehicles but using these vehicles for the operation may damage the environmental creditability of BSSs. A methodology is needed to mitigate the environmental impact of this operation.
This study aims to propose a methodology to reposition both good and broken bikes in a bike-sharing network in order to achieve a perfect balance between bike demand and supply at each station and make sure that all broken bikes are moved back to the depot. The objective of this repositioning operation is to minimize the total CO2 emissions of all repositioning vehicles. A Mixed Integer Linear Program (MILP) model is presented to formulate the problem mentioned above and a commercial solver is used to solve it for small applications. Using example applications, problem characteristics and the factors that affect the CO2 emissions are discussed. The results indicate that allowing multiple visits can reduce vehicle emissions. Moreover, when the percentage of broken bikes in the system increases, the CO2 emissions increase. Furthermore, if there is a tolerance for meeting the demand target, when this tolerance increases, the CO2 emissions decrease. In addition, when the distance of a link in an optimal route increases, the resultant emissions may remain unchanged. Besides, when the vehicle capacity increases, the CO2 emissions decrease. The real world instances of Citybike Vienna are used to compare emission and distance minimization solutions and investigate the runtime complexity of the proposed model. The results demonstrate that a shorter distance may not necessarily lead to lower emissions. The results also show that as the number of vehicles increases, the total emissions and runtime increase. A clustering method based on the nearest neighbor heuristic together with a commercial solver is used to solve a large real-world instance. This result confirms the possibility of using the clustering approach to reduce the running time for large network instances with multiple vehicles.
自行车共享系统（BSS）和环境问题在交通运营中日益受到欢迎。在BSS中，自行车需求的分布往往与自行车供应不匹配，并且有坏自行车。可用的自行车需要在各个站点之间重新分配，以满足需求，所有损坏的自行车都需要运回仓库进行维修。这两种类型的自行车通常由化石燃料车辆运输，但使用这些车辆进行操作可能会损害BSS的环境信誉。需要一种方法来减轻该操作的环境影响。
本研究旨在提出一种方法，以重新定位共享单车网络中的好自行车和坏自行车，从而在每个站点实现自行车需求和供应之间的完美平衡，并确保所有坏自行车都被送回停车场。该重新定位操作的目标是将所有重新定位车辆的总CO2排放量降至最低。提出了一个混合整数线性规划（MILP）模型来表达上述问题，并使用商业求解器来解决小应用中的问题。通过实例应用，讨论了问题特征和影响CO2排放的因素。结果表明，允许多次访问可以减少车辆排放。此外，当系统中坏自行车的百分比增加时，二氧化碳排放量也会增加。此外，如果存在满足需求目标的公差，则当该公差增加时，CO2排放量减少。此外，当最佳路线中的路段距离增加时，产生的排放量可能保持不变。此外，当车辆容量增加时，CO2排放量减少。Citybike Vienna的真实世界实例用于比较排放和距离最小化解决方案，并研究所提出模型的运行时复杂性。结果表明，较短的距离不一定会导致较低的排放。结果还表明，随着车辆数量的增加，总排放量和运行时间都会增加。基于最近邻启发式的聚类方法与商业求解器一起用于求解大型真实世界实例。该结果证实了使用聚类方法来减少具有多个车辆的大型网络实例的运行时间的可能性。

—### 28.TI A static free-floating bike repositioning problem with multiple heterogeneous vehicles, multiple depots, and multiple visits

• 多异质车辆、多站点和多次访问的静态自由浮动自行车重定位问题
• AU Liu, Y; Szeto, WY; Ho, SC
  AF Liu, Ying; Szeto, W. Y; Ho, Sin C.
• SO TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• PY 2018

AB In this paper, a bike repositioning problem with multiple depots, multiple visits, and multiple heterogeneous vehicles for the free-floating bike-sharing system (FFBSS) is studied. Two types of nodes (i.e., easily and hardly access nodes) with different penalties are defined to represent different convenience levels of getting bikes from the FFBSS. The objective of the repositioning is to minimize the weighted sum of the inconvenience level of getting bikes from the system and the total unmet demand and the total operational time. To solve this problem, an enhanced version of chemical reaction optimization (CRO) is developed. A loading and unloading quantity adjustment procedure with the consideration of the node characteristics, including the type of node and its current state (i.e., in a balanced, surplus, or deficit state) is proposed and incorporated into this version to improve its solution quality. A concept of the nearby-node set is also proposed to narrow the search space. Numerical results are presented and indicate that compared to the traditional CRO and CPLEX, the enhanced CRO improves solution quality and has potential to tackle the repositioning problem for larger, longer repositioning duration, and more vehicle instances. The results also demonstrate the effectiveness of the proposed adjustment procedure.

本文研究了自由浮动共享单车系统（FFBSS）中具有多个站点、多个访问和多个异构车辆的自行车重新定位问题。定义了具有不同惩罚的两种类型的节点（即容易和难以访问的节点），以表示从FFBSS获取自行车的不同便利程度。重新定位的目标是最小化从系统中获取自行车的不便程度与未满足的总需求和总运营时间的加权和。为了解决这个问题，开发了化学反应优化（CRO）的增强版本。提出了考虑节点特性（包括节点类型及其当前状态（即处于平衡、盈余或赤字状态）的加载和卸载量调整程序，并将其纳入本版本，以提高其解决方案质量。还提出了邻近节点集的概念来缩小搜索空间。数值结果表明，与传统的CRO和CPLEX相比，增强的CRO提高了解决方案的质量，并有潜力解决更大、更长的重新定位时间和更多车辆实例的重新定位问题。结果还证明了拟议调整程序的有效性。

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29.TI A clustering-based approach for balancing and scheduling bicycle-sharing systems

• 一种基于聚类的自行车共享系统平衡和调度方法
• AU Kacem, I; Kadri, A; Laroche, P
  AF Kacem, Imed; Kadri, Ahmed; Laroche, Pierre
• SO INTELLIGENT AUTOMATION AND SOFT COMPUTING
• PY 2018

AB This paper addresses an inventory regulation problem in bicycle sharing-systems. The problem is to balance a network consisting of a set of stations by using a single vehicle, with the aim of minimizing the weighted sum of the waiting times during which some stations remain imbalanced. Motivated by the complexity of this problem, we propose a two-stage procedure based on decomposition. First, the network is divided into multiple zones by using two different clustering strategies. Then, the balancing problem is solved in each zone. Finally, the order in which the zones must be visited is defined. To solve these problems, different algorithms based on approximate, greedy and exact methods are developed. The numerical results show the effectiveness of the proposed regulation methodology.

本文研究自行车共享系统中的库存管理问题。问题是用一辆车来平衡由一组站点组成的网络，目标是最小化一些站点保持不平衡的等待时间的加权和。由于这个问题的复杂性，我们提出了一个基于分解的两阶段过程。首先，使用两种不同的聚类策略将网络划分为多个区域。然后，在每个区域中解决平衡问题。最后，定义了必须访问区域的顺序。为了解决这些问题，基于近似、贪婪和精确方法的不同算法被开发出来。数值结果表明了所提出的调节方法的有效性

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30.TI Exact loading and unloading strategies for the static multi-vehicle bike repositioning problem

• 静态多车自行车重定位问题的精确装卸策略
• AU Szeto, WY; Shui, CS
  AF Szeto, W. Y.;Shui, C. S.
• SO TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
• PY 2018

AB This study investigates a bike repositioning problem (BRP) that determines the routes of the repositioning vehicles and the loading and unloading quantities at each bike station to firstly minimize the positive deviation from the tolerance of total demand dissatisfaction (TDD) and then service time. The total demand dissatisfaction of a bike-sharing system in this study is defined as the sum of the difference between the bike deficiency and unloading quantity of each station in the system. Two service times are considered: the total service time and the maximum route duration of the fleet. To reduce the computation time to solve the loading and unloading sub-problem of the BRP, this study examines a novel set of loading and unloading strategies and further proves them to be optimal for a given route. This set of strategies is then embedded into an enhanced artificial bee colony algorithm to solve the BRP. The numerical results demonstrate that a larger fleet size may not lead to a lower total service time but can effectively lead to a lower maximum route duration at optimality. The results also illustrate the trade-offs between the two service times, between total demand dissatisfaction and total service time, and between the number of operating vehicles provided and the TDD. Moreover, the results demonstrate that the optimal values of the two service times can increase with the TDD and introducing an upper bound on one service time can reduce the optimal value of the other service time. © 2018 The Authors. Published by Elsevier Ltd.

本研究研究了自行车重新定位问题（BRP），该问题确定了重新定位车辆的路线以及每个自行车站的装载和卸载量，以首先最小化与总需求不满意容忍度（TDD）和服务时间的正偏差。在本研究中，共享单车系统的总需求不满被定义为系统中每个站点的自行车不足量和卸载量之间的差值之和。考虑两个服务时间：车队的总服务时间和最长路线持续时间。为了减少求解BRP装载和卸载子问题的计算时间，本研究研究了一组新的装载和卸载策略，并进一步证明它们对于给定路线是最优的。然后将这组策略嵌入到增强的人工蜂群算法中，以解决BRP。数值结果表明，较大的车队规模可能不会导致较低的总服务时间，但可以有效地导致较短的最优性最大路线持续时间。结果还说明了两种服务时间之间的权衡，总需求不满与总服务时间之间，以及提供的运营车辆数量与TDD之间的权衡。此外，结果表明，两个服务时间的最优值可以随着TDD的增加而增加，并且在一个服务时间上引入上限可以降低另一个服务的最优值。（C） 2018作者。爱思唯尔有限公司出版。

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31.TI A Dynamic Approach to Rebalancing Bike-Sharing Systems

• 重新平衡自行车共享系统的动态方法
• AU Chiariotti, F; Pielli, C;Zanella, A; Zorzi, M
  AF Chiariotti, Federico; Pielli, Chiara; Zanella, Andrea; Zorzi, Michele
• SO SENSORS
• PY 2018

AB Bike-sharing services are flourishing in Smart Cities worldwide. They provide a low-cost and environment-friendly transportation alternative and help reduce traffic congestion. However, these new services are still under development, and several challenges need to be solved. A major problem is the management of rebalancing trucks in order to ensure that bikes and stalls in the docking stations are always available when needed, despite the fluctuations in the service demand. In this work, we propose a dynamic rebalancing strategy that exploits historical data to predict the network conditions and promptly act in case of necessity. We use Birth-Death Processes to model the stations’ occupancy and decide when to redistribute bikes, and graph theory to select the rebalancing path and the stations involved. We validate the proposed framework on the data provided by New York City’s bike-sharing system. The numerical simulations show that a dynamic strategy able to adapt to the fluctuating nature of the network outperforms rebalancing schemes based on a static schedule.

共享单车服务在全球智能城市蓬勃发展。它们提供了一种低成本、环境友好的交通方式，有助于减少交通拥堵。然而，这些新服务仍在开发中，需要解决几个挑战。一个主要问题是重新平衡卡车的管理，以确保停靠站的自行车和摊位在需要时始终可用，尽管服务需求波动。在这项工作中，我们提出了一种动态再平衡策略，该策略利用历史数据来预测网络状况，并在必要时及时采取行动。我们使用出生-死亡过程来模拟站点的占用率，并决定何时重新分配自行车，使用图论来选择重新平衡路径和涉及的站点。我们根据纽约市自行车共享系统提供的数据验证了所提出的框架。数值模拟表明，能够适应网络波动性质的动态策略优于基于静态调度的再平衡方案。

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32.TI Rebalance Modern Bike Sharing System: Spatio-Temporal Data Prediction

and Path Planning for Multiple Carriers

• 重新平衡现代自行车共享系统:时空数据预测 和多载波的路径规划
• AU Qin, RS;Kong, LH;Guo, MY;Yao, B;Guizani, M
  AF Qin, Rongshen; Kong, Linghe;Guo, Minyi;Yao, Bin; Guizani, Mohsen;GP IEEE
• SO 2018 IEEE 24TH INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED
• PY 2018

AB Modern bike sharing system, in which bikes can be parked freely, extends the flexibility of traditional bike sharing system and thus has greatly facilitated urban transportation. However, the balance of such system is often broken by the user behaviors. And how to manage a large number of bikes which parked randomly in a city is a difficult problem. To tackle this problem, we propose a two-step solution. First, we deal with the bike trajectory data and design the Spatial-Temporal Bike Flow Prediction (ST-BFP) model, which is a convolutional network based on residual framework with history external factors to predict the bike flows. Second, to make the system return to balance state as soon as possible, we propose an Improved Local Search Algorithm (ILSA) for path planning with multiple carriers based on forecast result, which schedules multiple carriers in real time to complete the rebalance task collaboratively. Finally, we validate our model and algorithm via realdata based experiment. Experimental results demonstrate that our method can balance the entire system efficiently.

现代自行车共享系统，自行车可以自由停放，扩展了传统自行车共享系统的灵活性，从而极大地促进了城市交通。然而，这种系统的平衡常常被用户行为打破。如何管理城市中随意停放的大量自行车是一个难题。为了解决这个问题，我们提出了两步解决方案。首先，我们处理自行车轨迹数据，并设计了时空自行车流量预测（ST-BFP）模型，该模型是基于残差框架的卷积网络，具有历史外部因素，用于预测自行车流量。其次，为了使系统尽快恢复到平衡状态，我们提出了一种基于预测结果的多载波路径规划的改进局部搜索算法（ILSA），该算法实时调度多个载波以协同完成再平衡任务。最后，我们通过基于真实数据的实验验证了我们的模型和算法。实验结果表明，该方法可以有效地平衡整个系统。

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###33.TI Stochastic fleet deployment models for public bicycle rental systems

• 公共自行车租赁系统的随机车队部署模型
• AU Yan, SY; Lu, CC;Wang, MH
  AF Yan, Shangyao; Lu, Chung-Cheng;Wang, Min-Hung
• SO INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
• PY 2018

AB This paper presents two stochastic bike deployment (SBD) models that determine the optimal number of bicycles allocated to each station in a leisure-oriented public bicycle rental system with stochastic demands. The SBD models represent the stochastic demands using a set of scenarios with given probabilities. A multilayer bike-flow time-space network is constructed for developing the models, where each layer corresponds to a given demand scenario and effectively describes bicycle flows in the spatial and temporal dimensions. As a result, the models are formulated as the integer multi-commodity network flow problem, which is characterized as NP-hard. We propose a heuristic to efficiently obtain good quality solutions for large-size model instances. Test instances are generated using real data from a bicycle rental system in Taiwan to evaluate the performance of the models and the solution algorithm. The test results show that the models can help the system operator of a public bicycle system make effective fleet deployment decisions.

本文提出了两个随机自行车部署（SBD）模型，以确定在具有随机需求的面向休闲的公共自行车租赁系统中分配给每个站点的自行车的最佳数量。SBD模型使用一组给定概率的情景来表示随机需求。为了开发模型，构建了多层自行车流时空网络，其中每个层对应于给定的需求场景，并在空间和时间维度上有效地描述自行车流。因此，模型被表述为整数多商品网络流问题，其特征为NP困难。我们提出了一种启发式方法，以有效地获得大型模型实例的高质量解决方案。使用来自台湾自行车租赁系统的真实数据生成测试实例，以评估模型和解决算法的性能。测试结果表明，该模型可以帮助公共自行车系统的系统操作员做出有效的车队部署决策。

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###34.TI Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

• 自行车共享系统中需求预测和出行可视化的多智能体系统
• AU Lozano, A; De Paz, JF; Gonzalez, GV;De la Iglesia, DH;Bajo, J
  AF Lozano, Alvaro; De Paz, Juan F.; Villarrubia Gonzalez, Gabriel; De la Iglesia, Daniel H.;Bajo, Javier
• SO APPLIED SCIENCES-BASEL
• PY 2018

AB This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each bicycle station. Moreover, the architecture offers API (Application Programming Interface) services and provides a web application for visualization and forecasting. This work aims to make the system generic enough for it to be able to integrate data from different types of bike sharing systems. Thus, in future studies it will be possible to employ the proposed system in different types of bike sharing systems. This article contains a literature review, a section on the process of developing the system and the built-in prediction models. Moreover, a case study which validates the proposed system by implementing it in a public bicycle sharing system in Salamanca, called SalenBici. It also includes an outline of the results and conclusions, a discussion on the challenges encountered in this domain, as well as possibilities for future work.

本文提出了一种为共享单车系统（BSS）提供可视化和预测工具的多代理系统。所提出的多智能体系统包括一个执行数据收集和清洁过程的智能体，它还能够为每个自行车站创建需求预测模型。此外，该架构提供API（应用程序编程接口）服务，并提供用于可视化和预测的web应用程序。这项工作旨在使该系统具有足够的通用性，以便能够集成来自不同类型共享单车系统的数据。因此，在未来的研究中，将有可能在不同类型的自行车共享系统中使用所提出的系统。本文包括文献综述、系统开发过程和内置预测模型的一节。此外，一个案例研究通过在萨拉曼卡的公共自行车共享系统SalenBici中实施，验证了所提出的系统。报告还概述了结果和结论，讨论了在这一领域遇到的挑战，以及未来工作的可能性。

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###35.TI A Circuit Constraint for Multiple Tours Problems

• 多重旅行问题的电路约束
• AU Vismara, P; Briot, N
  AF Vismara, Philippe;Briot, Nicolas;BE Hooker, J
• SO PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING
• PY 2018

AB Routing problems appear in many practical applications. In the context of Constraint Programming, circuit constraints have been successfully developed to handle problems like the well-known Traveling Salesman Problem or the Vehicle Routing Problem. These kind of constraints are linked to the search for a Hamiltonian circuit in a graph. In this paper we consider a more general multiple tour problem that consists in covering a part of the graph with a set of minimal cost circuits. We define a new global constraint WEIGHTEDSUBCIRCUITS that generalizes the WeightedCircuit constraint by releasing the need to obtain a Hamiltonian circuit. It enforces multiple disjoint circuits of bounded total cost to partially cover a weighted graph, the subsets of vertices to be covered being induced by external constraints. We show that enforcing Bounds Consistency for WeightedSubCircuits is NP-hard. We propose an incomplete but polynomial filtering method based on the search for a lower bound of a weighted Steiner circuit.

路由问题出现在许多实际应用中。在约束编程的背景下，电路约束已经被成功地开发，以处理诸如众所周知的旅行推销员问题或车辆路线问题之类的问题。这些约束与在图中搜索哈密顿回路有关。在本文中，我们考虑一个更一般的多重旅行问题，即用一组最小成本电路覆盖图的一部分。我们定义了一个新的全局约束WEIGHTEDSUBCIRCUITS，该约束通过释放获得哈密顿电路的需要来推广WeightedCircuit约束。它强制总成本有界的多个不相交电路部分覆盖加权图，要覆盖的顶点子集由外部约束诱导。我们证明了加强加权子电路的边界一致性是NP困难的。我们提出了一种基于搜索加权Steiner电路下界的不完全多项式滤波方法。

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36.TI A time-space network flow approach to dynamic repositioning in bicycle sharing systems

• 自行车共享系统动态再定位的时空网络流方法
• AU Zhang, D; Yu, CH; Desai, J;Lau, HYK; Srivathsan, S
  AF Zhang, Dong; Yu, Chuhang;Desai, Jitamitra; Lau, H. Y. K.;Srivathsan, Sandeep
• SO TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
• PY 2017

AB Faced with increasing population density, rising traffic congestion, and the resulting upsurge in carbon emissions, several urban metropolitan areas have instituted public bicycle sharing system as a viable alternative mode of transportation to complement existing long-distance bus- and metro-transit systems. A pressing issue that needs to be addressed in bike sharing systems is the accrued imbalance of bicycles between commuter demands and inventory levels at stations. To overcome this issue, a commonly employed strategy is to reposition bicycles during off-peak periods (typically at night) when no new user arrivals are expected. However, when such an imbalance occurs during day-time peak hours, such a passive strategy would result in lower resource utilization rates. To overcome this drawback, in this study, we propose a dynamic bicycle repositioning methodology that considers inventory level forecasting, user arrivals forecasting, bicycle repositioning, and vehicle routing in a unified manner. A multi-commodity time-space network flow model is presented, which results in an underlying complex nonlinear optimization problem. This problem is then reformulated into an equivalent mixed-integer problem using a model transformation approach and a novel heuristic algorithm is proposed to efficiently solve this model. Specifically, the first stage involves solving the linear relaxation of the MIP model, and a set covering problem is subsequently solved in the second stage to assign routes to the repositioning vehicles. The proposed methodology is evaluated using standard test-bed instances from the literature, and our numerical results reveal that the heuristic algorithm can achieve a significant reduction in rejected user requests when compared to existing methods, while yet expending only minimal computational effort. © 2016 Elsevier Ltd. All rights reserved.

面对日益增加的人口密度、日益严重的交通拥堵以及由此产生的碳排放激增，一些城市大都会地区已经建立了公共自行车共享系统，作为一种可行的替代交通方式，以补充现有的长途公共汽车和地铁交通系统。共享单车系统需要解决的一个紧迫问题是，通勤需求和车站库存水平之间的自行车累积失衡。为了克服这一问题，通常采用的策略是在非高峰时段（通常在夜间）重新定位自行车，因为预计不会有新的用户到达。然而，当这种不平衡发生在白天高峰时段时，这种被动策略将导致资源利用率降低。为了克服这一缺陷，在本研究中，我们提出了一种动态自行车重新定位方法，该方法以统一的方式考虑库存水平预测、用户到达预测、自行车重新定位和车辆路线。提出了一种多商品时空网络流模型，该模型导致了一个潜在的复杂非线性优化问题。然后使用模型变换方法将该问题重新表述为等效的混合整数问题，并提出了一种新的启发式算法来有效地解决该模型。具体地，第一阶段涉及解决MIP模型的线性松弛，并且随后在第二阶段中解决集合覆盖问题，以向重新定位的车辆分配路线。使用文献中的标准试验台实例对所提出的方法进行了评估，我们的数值结果表明，与现有方法相比，启发式算法可以显著减少被拒绝的用户请求，同时只花费最小的计算工作量。（C） 2016爱思唯尔有限公司版权所有。

###37.TI A Dynamic Programming Model for Operation Decision-Making in Bicycle
Sharing Systems under a Sustainable Development Perspective

• 自行车运营决策的动态规划模型 可持续发展视角下的共享系统
• AU Li, LF;Shan, MY; Li, Y; Liang, S
  AF Li, Linfeng; Shan, Miyuan; Li, Ying; Liang, Sheng
• SO SUSTAINABILITY
• PY 2017

AB Maintaining a balance between revenue and expenditure is the key to the sustainable development of a bicycle sharing system (BSS), and is a challenge for almost all systems worldwide. This article proposes a dynamic programming approach to obtain the optimal strategy to maximize the revenue of overall BSS. The Variable Granularity-Depth First Search (VG-DFS) algorithm is designed to speed up the solution. A numerical experiment is presented to verify the applicability of the model through a comparison with real data from the BSS in Hangzhou. Results indicated that the BSS could achieve break-even, or even obtain a substantial income by utilizing our model to make operational decisions, especially when the region it is located in has a relatively high GDP. Moreover, the best investment strategy proved is to involve stations in the initial construction period of the BSS as much as possible.

保持收支平衡是共享单车系统（BSS）可持续发展的关键，也是全球几乎所有系统面临的挑战。本文提出了一种动态规划方法，以获得使整个BSS收入最大化的最优策略。可变粒度深度优先搜索（VG-DFS）算法被设计用于加快解决方案。通过与杭州BSS的实际数据的比较，给出了一个数值实验，以验证该模型的适用性。结果表明，通过利用我们的模型进行运营决策，特别是当其所在地区的GDP相对较高时，BSS可以实现盈亏平衡，甚至获得可观的收入。此外，已证明的最佳投资策略是在BSS的初始建设期内尽可能让站点参与。

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38.TI Towards Dynamic Rebalancing of Bike Sharing Systems: An Event-Driven

Agents Approach

• 自行车共享系统的动态再平衡:事件驱动 代理方法
• AU Dotterl, J; Bruns, R; Dunkel, J; Ossowski, S
  AF Doetterl, Jeremias; Bruns, Ralf;Dunkel, Juergen; Ossowski, Sascha
  BE Oliveira, E; Gama, J; Vale, Z; Cardoso, HL
• SO PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2017)
• PY 2017

AB Operating a Bicycle Sharing System over some time without the operator’s intervention causes serious imbalances, which prevents the rental of bikes at some stations and the return at others. To cope with such problems, user-based bicycle rebalancing approaches offer incentives to influence the users’ behavior in an appropriate way. In this paper, an event-driven agent architecture is proposed, which uses Complex Event Processing to predict the future demand at the bike stations using live data about the users. The predicted demands are used to derive situation-aware incentives that are offered by the affected stations. Furthermore, it is shown how bike stations cooperate to prevent that they outbid each other.

在没有运营商干预的情况下，在一段时间内运行自行车共享系统会导致严重的不平衡，这会阻止在某些站点租赁自行车，而在其他站点归还自行车。为了解决这些问题，基于用户的自行车再平衡方法提供了激励措施，以适当的方式影响用户的行为。在本文中，提出了一种事件驱动的代理体系结构，该体系结构使用复杂事件处理来使用用户的实时数据预测自行车站的未来需求。预测需求用于获得受影响电站提供的态势感知激励。此外，它还展示了自行车站如何合作，以防止它们彼此出价过高。

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39.TI Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems

• 动态重新定位以减少自行车共享系统中的需求损失
• AU Ghosh, S; Varakantham, P;Adulyasak, Y; Jaillet, P
  AF Ghosh, Supriyo; Varakantham, Pradeep; Adulyasak, Yossiri; Jaillet, Patrick
• SO JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
• PY 2017

AB Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of non-renewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing data has shown that congestion/starvation is a common phenomenon that leads to a large number of unsatisfied customers resulting in a significant loss in customer demand. In order to tackle this problem, we propose an optimisation formulation to reposition bikes using vehicles while also considering the routes for vehicles and future expected demand. Furthermore, we contribute two approaches that rely on decomposability in the problem (bike repositioning and vehicle routing) and aggregation of base stations to reduce the computation time significantly. Finally, we demonstrate the utility of our approach by comparing against two benchmark approaches on two real-world data sets of bike sharing systems. These approaches are evaluated using a simulation where the movements of customers are generated from real-world data sets.

自行车共享系统（BSS）在世界主要城市被广泛采用，原因是与大量私人车辆使用相关的担忧，即碳排放增加、交通拥堵和不可再生资源的使用。在BSS中，基站被战略性地放置在整个城市，每个基站在一天开始时都储备有预定数量的自行车。客户从一个站点租用自行车，然后在另一个站点归还。由于租用自行车的客户不可预测的移动，基站的自行车要么拥挤（超过要求），要么匮乏（低于要求）。现有数据表明，拥挤/饥饿是一种常见现象，会导致大量不满意的客户，从而导致客户需求的严重损失。为了解决这个问题，我们提出了一个优化公式，以重新定位使用车辆的自行车，同时考虑车辆的路线和未来的预期需求。此外，我们提出了两种方法，它们依赖于问题中的可分解性（自行车重新定位和车辆路线）和基站的聚合来显著减少计算时间。最后，我们通过在共享单车系统的两个真实数据集上与两个基准方法进行比较，证明了我们方法的实用性。这些方法使用模拟进行评估，其中客户的移动是从真实世界数据集生成的。

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40.TI Constraint-Based Fleet Design Optimisation for Multi-compartment

Split-Delivery Rich Vehicle Routing

• 基于约束的多舱车队设计优化 分批交付丰富的车辆路径
• AU Urli, T;Kilby, P
  AF Urli, Tommaso; Kilby, Philip
  BE Beck, JC
• SO PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING (CP 2017)
• PY 2017

AB We describe a large neighbourhood search (LNS) solver based on a constraint programming (CP) model for a real-world rich vehicle routing problem with compartments arising in the context of fuel delivery. Our solver supports both single-day and multi-day scenarios and a variety of real-world aspects including time window constraints, compatibility constraints, and split deliveries. It can be used both to plan the daily delivery operations, and to inform decisions on the long-term fleet composition. We show experimentally the viability of our approach.

我们描述了一个基于约束规划(CP)模型的大邻域搜索(LNS)求解器，用于解决现实世界中燃料运输中的多车厢车辆路径问题。我们的求解器支持单日和多日场景以及各种现实情况，包括时间窗约束、兼容性约束和分批交付。它既可用于规划日常交付作业，也可用于为长期车队构成决策提供信息。我们通过实验证明了我们方法的可行性。

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41.TI Bidirectional Incentive Model for Bicycle Redistribution of a Bicycle

Sharing System during Rush Hour

• 自行车再分配的双向激励模型 高峰时间的共享系统
• AU Li, LF; Shan, MY
  AF Li, Linfeng;Shan, Miyuan
• SO SUSTAINABILITY
• PY 2016

AB Redistribution is an important part of operational activities in a bicycle sharing system (BSS). This paper proposes that there are two types of users in a BSS: leisure travelers and commuters. The operators and the government are adopting the bidirectional incentive model (BIM) to improve their service level of redistribution. That is, the BIM stimulates leisure travelers to actively respond to bicycle resetting needs of the system; on the other hand, it guides commuters by encouraging them to avoid travelling in peak periods. This is beneficial to achieve the goals of reducing the scheduling pressure on bicycles during rush hour, and even to realize the self-resetting of the BSS. In this paper, we explore three scenarios for implementing BIM through cooperation between the operator and the government. By exploiting Stackelberg games in all models, we illustrate the quantity of users in three different travel behaviors, and surplus value of these users respectively. We also consider the trend of the profit of the operator and the government when some changes of parameters are made. The numerical analysis and case discussion find that the strategy of the operator implementing BIM with a subsidy is the best method for developed regions. In a developing region, the strategy of implementing the BIM with a direct government subsidy to users is the best choice in a small or tourist city. In these cities, the proportion of leisure travelers is always larger than 50%, resulting in a significant incentive effect. The strategy of the operator implementing BIM without a subsidy is the best choice for the large and medium-sized city.

再分配是自行车共享系统（BSS）运营活动的重要组成部分。本文提出BSS中有两种类型的用户：休闲旅行者和通勤者。运营商和政府正在采用双向激励模型（BIM），以提高其再分配服务水平。也就是说，BIM刺激休闲旅行者积极响应系统的自行车重置需求；另一方面，它通过鼓励通勤者避免在高峰时段出行来引导他们。这有利于实现减少高峰时段自行车调度压力的目标，甚至实现BSS的自动重置。在本文中，我们探讨了通过运营商和政府之间的合作实施BIM的三种场景。通过在所有模型中使用Stackelberg游戏，我们分别说明了三种不同旅行行为中的用户数量以及这些用户的剩余价值。我们还考虑了当参数发生一些变化时，运营商和政府的利润趋势。数值分析和案例讨论发现，运营商利用补贴实施BIM的策略是发达地区的最佳方法。在一个发展中的地区，在一个小城市或旅游城市中，实施BIM并向用户提供政府直接补贴的策略是最佳选择。在这些城市，休闲旅行者的比例始终大于50%，从而产生了显著的激励效应。运营商在无补贴的情况下实施BIM的策略是大中型城市的最佳选择。