Bibliography
[recommendation] a literature survey of various extensions of the VRP occurring in practice :
- O. Bräysy, M. Gendreau, G. Hasle and A. Løkketangen. “A Survey of Heuristics for the Vehicle Routing Problem, Part I: Basic Problems and Supply Side Extensions”.
- O. Bräysy, M. Gendreau, G. Hasle and A. Løkketangen. “A Survey of Heuristics for the Vehicle Routing Problem, Part II: Demand Side Extensions”.
TSP heuristics
(Flood, 1956; Lin, 1965; Lin and Kernighan, 1973; Bentley, 1990;Bentley,1992;Reinelt,1994;Johnson and McGeoch, 1997)
Simulated Annealing
(Kirkpatrick et al., 1983; van Laarhoven and Aarts, 1987; Reeves, 1993; Johnson and McGeoch, 1997)
Tabu Search
(Glover, 1989a; Glover, 1989b; Taillard, 1991; Reeves, 1993; Battiti and Tecchiolli, 1994; Glover and Laguna, 1998; Taillard, 1997)
Fitness Landscapes
(Wright, 1932; Kauffman and Levin, 1987; Weinberger, 1990; Kauffman, 1993; Jones and Forrest, 1995; Stadler, 1995)
Evolutionary Algorithms
(Goldberg, 1989; Rechenberg, 1973; Fogel, 1995; B¨ack, 1996; Michalewicz, 1996; B¨ack et al., 1997b; Michalewicz and Fogel, 1999; B¨ack et al., 1997a; Heitk¨otter and Beasley, 2001)
Memetic Algorithms
(Moscato, 1989; Merz and Freisleben, 1999; Moscato, 1999; Merz, 2000; Merz and Freisleben, 2002; Merz, 2001; Moscato, 2001)
Differential Evolution
(Storn and Price, 1995; Price, 1996; Storn, 1996; Price and Storn, 1997; Price, 1999)
Particle Swarm Optimization
(Kennedy and Eberhart, 1995; Angeline, 1998; Eberhart and Shi, 1998; Kennedy and Eberhart, 1999)
Bit-Simulated Crossover and Population-based Incremental Learning
(Syswerda, 1993; Baluja, 1994; Baluja and Caruana, 1995; Baluja, 1997; Monmarch´e et al., 1999)
Ant Colony Optimization
(Dorigo et al., 1991; Dorigo et al., 1996; Dorigo and Gambardella, 1997; St¨utzle and Hoos, 1997; Dorigo and Di Caro, 1999)
Iterated Local Search and Variable Neighboorhood Search
(Baum, 1986; Martin et al., 1991; Martin and Otto, 1996; Hansen and Mladenovi`c, 1997; Hansen and Mladenovi`c, 1998; Lourenco et al., 2001; Lourenco et al., 2002)
Scatter Search and Path Relinking
(Glover, 1968; Glover, 1994; Glover, 1998; Glover, 1999; Laguna, 2002)
*********************************************************
References
Angeline, P. J. (1998). Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences. In Porto, V. W., Saravanan, N., Waagen, D., and Eiben, A. E., editors, Evolutionary Programming VII, pages 601–610, Berlin. Springer. Lecture Notes in Computer Science 1447.
B¨ack, T. (1996). Evolutionary Algorithms in Theory and Practice. Oxford University Press.
B¨ack, T., Fogel, D. B., and Michalewicz, Z. (1997a). Handbook of Evolutionary Computation. Oxford University Press.
B¨ack, T., Hammel, U., and Schwefel, H.-P. (1997b). Evolutionary Computation: Comments on the History and Current State. IEEE Transactions on Evolutionary Computation, 1(1):3–17.
Baluja, S. (1994). Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning. Technical Report CS-94-163, Carnegie Mellon University, School of Computer Science.
Baluja, S. (1997). Genetic Algorithms and Explicit Search Statistics. In Mozer, M. C., Jordan, M. I., and Petsche, T., editors, Advances in Neural Information Processing Systems 9, pages 319–325, Cambridge, MA. MIT Press.
Baluja, S. and Caruana, R. (1995). Removing the Genetics from the Standard Genetic Algorithm. In Prieditis, A. and Russel, S., editors, Proceedings of the International Conference on Machine Learning, 1995, pages 38–46, San Mateo, CA. Morgan Kaufmann Publishers.
Battiti, R. and Tecchiolli, G. (1994). The Reactive Tabu Search. ORSA Journal on Computing, 6(2):126–140.
Baum, E. B. (1986). Towards Practical “Neural” Computation for Combinatorial Optimization Problems. In Denker, J. S., editor, Neural Networks for Computing, pages 53–58, Snowbird 1986.
American Institute of Physics, New York.
Bentley, J. L. (1990). Experiments on Traveling Salesman Heuristics. In Proceedings of the First Annual ACM-SIAM Symposium on Discrete Algorithms, pages 91–99.
Bentley, J. L. (1992). Fast Algorithms for Geometric Traveling Salesman Problems. ORSA Journal on Computing, 4(4):387–411.
Dorigo, M. and Di Caro, G. (1999). The Ant Colony Optimization Meta-Heuristic. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 11–32. McGraw–Hill.
Dorigo, M. and Gambardella, L. M. (1997). Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation, 1(1):53–66.
Dorigo, M., Maniezzo, V., and Colorni, A. (1991). Positive Feedback as a Search Strategy. Technical Report 91–016, Politecnico di Milano, Milano, Italy.
Dorigo, M., Maniezzo, V., and Colorni, A. (1996). The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 26(1):29–41.
Eberhart, R. C. and Shi, Y. (1998). Comparison between Genetic Algorithms and Particle Swarm Optimization. In Porto, V.W., Saravanan, N.,Waagen, D., and Eiben, A. E., editors, Evolutionary Programming VII, pages 611–616, Berlin. Springer. Lecture Notes in Computer Science 1447.
Flood, M. M. (1956). The Traveling–Salesman Problem. Operations Research, 4:61–75.
Fogel, D. (1995). Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE.
Glover, F. (1968). Surrogate Constraints. Operations Research, 16(4):741–749.
Glover, F. (1989a). Tabu Search - Part 1. ORSA Journal on Computing, 1(3):190–206.
Glover, F. (1989b). Tabu search - Part 2. ORSA Journal on Computing, 2(1):4–32.
Glover, F. (1994). Genetic Algorithms And Scatter Search - Unsuspected Potentials. Statistics And Computing, 4(2):131–140.
Glover, F. (1998). A Template for Scatter Search and Path Relinking. In Hao, J.-K., Lutton, E., Ronald, E., Schoenauer, M., and Snyers, D., editors, Artificial Evolution, volume 1363 of Lecture Notes in Computer Science, pages 13–54.
Glover, F. (1999). Scatter Search and Path Relinking. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 297–316. McGraw-Hill, London.
Glover, F. and Laguna, M. (1998). Tabu Search. Kluwer Academic Publishers.
Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley.
Hansen, P. and Mladenovi`c, N. (1997). Variable Neighborhood Search. Computers and Operations Research, 24:1097–1100.
Hansen, P. and Mladenovi`c, N. (1998). An Introduction to Variable Neighborhood Search. In Voß, S., Martello, S., Osman, I. H., and Roucairol, C., editors, Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization. Proceedings of MIC 97 Conference. Kluwer Academic Publishers, Dordrecht, The Netherlands.
Heitk¨otter, J. and Beasley, D. (Issue 9.1, 2001). The Hitch-Hiker’s Guide to Evolutionary Computation. URL - http://surf.de.uu.net/encore/www/.
Johnson, D. S. and McGeoch, L. A. (1997). The Traveling Salesman Problem: A Case Study. In Aarts, E. H. L. and Lenstra, J. K., editors, Local Search in Combinatorial Optimization, pages 215–310. Wiley and Sons, New York.
Jones, T. and Forrest, S. (1995). Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms. In Eshelman, L. J., editor, Proceedings of the 6th International Conference on Genetic Algorithms, pages 184–192. Morgan Kaufmann.
Kauffman, S. A. (1993). The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press.
Kauffman, S. A. and Levin, S. (1987). Towards a General Theory of Adaptive Walks on Rugged Landscapes. Journal of Theoretical Biology, 128:11–45.
Kennedy, J. and Eberhart, R. C. (1995). Particle Swarm Optimization. In Proceedings of the IEEE International Conference on Neural Networks, pages 1942–1948, Piscataway, NJ. IEEE Service Center.
Kennedy, J. and Eberhart, R. C. (1999). The Particle Swarm: Social Adaptation in Information-Processing Systems. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 379–387. McGraw-Hill, London.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P. (1983). Optimization by Simulated Annealing. Science, 220:671–680.
Laguna, M. (2002). Scatter Search and Path Relinking. In Pardalos, P. M. and Resende, M. G. C., editors, Handbook of Applied Optimization, pages 183–193. Oxford University Press.
Lin, S. (1965). Computer Solutions of the Travelling Salesman Problem. Bell System Technical Journal, 44:2245–2269.
Lin, S. and Kernighan, B. (1973). An Effective Heuristic Algorithm for the Traveling Salesman Problem. Operations Research, 21:498–516.
Lourenco, H. R., Martin, O., and St¨utzle, T. (2001). A Beginner’s Introduction to Iterated Local Search. In Proceedings of the 4th Metaheuristics International Conference - MIC 2001, pages 1–6, Porto, Portugal.
Lourenco, H. R., Martin, O., and St¨utzle, T. (2002). Iterated Local Search. In Glover, F. and Kochenberger, G., editors, Handbook of Metaheuristics. to appear.
Martin, O., Otto, S. W., and Felten, E. W. (1991). Large-Step Markov Chains for the Traveling Salesman Problem. Complex Systems, 5:299–326.
Martin, O. C. and Otto, S.W. (1996). Combining Simulated Annealing with Local Search Heuristics. Annals of Operations Research, 63:57–75.
Merz, P. (2000). Memetic Algorithms for Combinatorial Optimization Problems: Fitness Landscapes and Effective Search Strategies. PhD thesis, Department of Electrical Engineering and Computer Science, University of Siegen, Germany.
Merz, P. (2001). On The Performance of Memetic Algorithms in Combinatorial Optimization. In Hart, W. E., Krasnogor, N., and Smith, J., editors, Second Workshop on Memetic Algorithms (WOMA II), Genetic and Evolutionary Computation Conference GECCO 2001, pages 168–173, San Francisco, CA. Morgan Kaufmann.
Merz, P. and Freisleben, B. (1999). Fitness Landscapes and Memetic Algorithm Design. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 245–260. McGraw–Hill, London.
Merz, P. and Freisleben, B. (2002). Memetic Algorithms for the Traveling Salesman Problem. Complex Systems. To appear.
Michalewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin.
Michalewicz, Z. and Fogel, D. B. (1999). How to Solve It: Modern Heuristics. Springer, Berlin.
Monmarch´e, N., Ramat, E., Dromel, G., Slimane, M., and Venturini, G. (1999). On the Similarities Between AS, BSC and PBIL: Toward the Birth of a New Meta-heuristic. Rapport interne 215, Laboratoire d’Informatique de l’Universit´e de Tours, Tours, France.
Moscato, P. (1989). On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms. Technical Report C3P Report 826, Caltech Concurrent Computation Program, California Institue of Technology.
Moscato, P. (1999). Memetic Algorithms: A Short Introduction. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 219–234. McGraw–Hill, London.
Moscato, P. (2001). The Memetic Algorithms´ Home Page, A Collection of Memetic Algorithms Resources. URL - http://www.ing.unlp.edu.ar/cetad/mos/memetic_home.html
Price, K. and Storn, R. (1997). Differential Evolution: A Simple Evolution Strategy for Fast Optimization. Dr. Dobb’s Journal, 22(4):18–24.
Price, K. V. (1996). Differential Evolution: A Fast and Simple Numerical Optimizer. In Smith, M. H., Lee, M. A., Keller, J., and Yen, J., editors, 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS, pages 524–527, Piscataway, NJ. IEEE Service Center.
Price, K. V. (1999). An Introduction to Differential Evolution. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 79–108. McGraw-Hill, London.
Rechenberg, I. (1973). Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog, Stuttgart.
Reeves, C. R. (1993). Modern Heuristic Techniques for Combinatorial Problems. McGraw Hill.
Reinelt, G. (1994). The Traveling Salesman: Computational Solutions for TSP Applications, volume 840 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, Germany.
Stadler, P. F. (1995). Towards a Theory of Landscapes. In Lop´ez-Pe˜na, R., Capovilla, R., Garc´ıa-Pelayo, R., Waelbroeck, H., and Zertuche, F., editors, Complex Systems and Binary Networks, volume 461 of Lecture Notes in Physics, pages 77–163, Berlin, New York. Springer Verlag.
Storn, R. (1996). On the Usage of Differential Evolution for Function Optimization. In Smith, M. H., Lee, M. A., Keller, J., and Yen, J., editors, 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS, pages 519–523, Piscataway, NJ. IEEE Press.
Storn, R. and Price, K. (1995). Differential Evolution - a Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces. Technical Report TR-95-012, Berkeley, CA.
St¨utzle, T. and Hoos, H. (1997). The MAX–MIN Ant System and Local Search for the Traveling Salesman Problem. In Baeck, T., Michalewicz, Z., and Yao, X., editors, Proceedings 1997 IEEE International Conference on Evolutionary Computation (ICEC’97), pages 309–314.
Syswerda, G. (1993). Simulated Crossover in Genetic Algorithms. In Whitley, D., editor, Proceedings of the Second Workshop on Foundations of Genetic Algorithms (FOGA II), pages 239–255. Morgan Kauffmann, San Mateo.
Taillard, ` E. (1997). Tabu Search. In Aarts, E. H. L. and Lenstra, J. K., editors, Local Search in Combinatorial Optimization, chapter 1, pages 1–17. Wiley.
Taillard, ´ E. D. (1991). Robust Taboo Search for the Quadratic Assignment Problem. Parallel Computing, 17:443–455.
van Laarhoven, P. J. M. and Aarts, E. H. L. (1987). Simulated Annealing: Theory and Applications. Kluwer Academic Publishers.
Weinberger, E. D. (1990). Correlated and Uncorrelated Fitness Landscapes and How to Tell the Difference. Biological Cybernetics, 63:325–336.
Wright, S. (1932). The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution. In Proceedings of the Sixth Congress on Genetics, volume 1, page 365, Brooklyn, New York.