旅行计划 c++_设计旅行计划器

旅行计划 c++

We love to travel. In exploring new places, we have opportunities to think about life and appreciate the beautiful world we live in. Meanwhile, there are many uncertainties and worries in any travel. People cannot help but ask questions like “did I use my time at some place wisely?” or “have I visited all the must-see places in some city?” Travel planning is one of the most important aspects of having a great experience.

我们喜欢旅行。 在探索新的地方时，我们有机会思考生活并欣赏我们所生活的美丽世界。与此同时，任何旅行都存在许多不确定性和忧虑。 人们不禁会问诸如“我是否在某个地方明智地利用了我的时间？”之类的问题。 或“我去过某个城市的所有必游景点吗？” 出行计划是拥有丰富经验的最重要方面之一。

A typical trip planning process starts with opening Google or Expedia and searching for hotels, flights and interesting places to visit and eat. After booking flight tickets and rental cars and possibly hotels, diligent travelers would start searching for places to spend each day. This is when real hassle begins. People often find them open tens of tabs in the browser comparing different places of interest and wonder how long they should stay at each place. Eventually the planning becomes so mind-boggling people would give up, or they finally come up with plans that are too aggressive to execute.

一个典型的旅行计划过程始于打开Goog​​le或Expedia并搜索酒店，航班和有趣的景点来用餐。 预订机票和租车以及可能的酒店后，勤奋的旅行者便会开始寻找每天度过的地方。 这是真正的麻烦开始的时候。 人们经常发现它们在浏览器中打开了数十个选项卡，将不同的景点进行比较，并想知道他们应该在每个位置停留多长时间。 最终，计划变得令人难以置信的人们放弃了，或者他们最终提出了过于激进的计划，无法执行。

问题范围 (Problem Scope)

The problem of developing a really good travel planner is very challenging, if not impossible to solve. For instance, there is no single plan for visiting Paris that works well for everyone. Some people prefer a more relaxed schedule, spending more time on fine-dining. And other people might want to focus on culture by devoting the majority of time in the Louvre Museum.

即使不是不可能解决，开发一个真正好的旅行计划者的问题也是非常具有挑战性的。 例如，没有一个适合所有人的访问巴黎的计划。 有些人喜欢更宽松的时间表，花更多的时间在美食上。 其他人可能希望通过在卢浮宫博物馆中花费大部分时间来关注文化。

As a hobby project, we do not attempt to build sophisticated machine-learning powered systems. Without a tremendous amount of data, those solutions are beyond reach. Instead we approach the problem from a pure computational point of view and allow a certain degree of customization. We design a distributed system with the execution power of Golang.

作为一个业余项目，我们不会尝试构建复杂的机器学习供电系统。 没有大量数据，这些解决方案是无法实现的。 取而代之的是，我们从纯粹的计算角度解决问题，并允许一定程度的自定义。 我们设计了具有Golang执行力的分布式系统。

The initial version of the travel plann