Combination and Comparison of Different Genetic Encodings for the Vehicle Routing Problem
Unlike for other problems, such as the traveling salesman problem, no widely accepted encodings for the vehicle routing problem have been developed yet. In this work, we examine different encodings and operations for vehicle routing problems. We show, how different encodings can be combined in one algorithm run and compare the individual encodings in terms of runtime and solution quality. Based on those results, we perform extensive test cases on different benchmark instances and show how the combination of different encodings and operations can be beneficial and provide a balance between solution quality and runtime.
Keywordsgenetic encoding vehicle routing problem
Unable to display preview. Download preview PDF.
- 1.Affenzeller, M., Wagner, S.: Offspring selection: A new self-adaptive selection scheme for genetic algorithms. In: Ribeiro, B., Albrecht, R.F., Dobnikar, A., Pearson, D.W., Steele, N.C. (eds.) Adaptive and Natural Computing Algorithms. Springer Computer Series, pp. 218–221. Springer, Heidelberg (2005)CrossRefGoogle Scholar
- 5.Cordeau, J.F., Gendreau, M., Hertz, A., Laporte, G., Sormany, J.S.: New heuristics for the vehicle routing problem. In: Logistics Systems: Design and Optimization, New York. ch.9, pp. 279–297 (2005)Google Scholar
- 12.Wagner, S.: Heuristic Optimization Software Systems - Modeling of Heuristic Optimization Algorithms in the HeuristicLab Software Environment. Ph.D. thesis, Johannes Kepler University, Linz, Austria (2009)Google Scholar
- 13.Zhu, K.Q.: A new genetic algorithm for vrptw. In: Proceedings of the International Conference on Artificial Intelligence, p. 311264 (2000)Google Scholar