Structural Synthesis of Dispatching Rules for Dynamic Dial-a-Ride Problems
The dial-a-ride problem consists of designing vehicle routes in the area of passenger transportation. Assuming that each vehicle can act autonomously, the problem can be modeled as a multi-agent system. In that context, it is a complex decision process for each agent to determine what action to perform next. In this work, the agent function is evolved using genetic programming by synthesizing basic bits of information. Specialized dispatching rules are synthesized automatically that are adapted to the problem environment. We compare the evolved rules with other dispatching strategies for dynamic dial-a-ride problems on a set of generated benchmark instances. Additionally, since genetic programming is a whitebox-based approach, insights can be gained about important system parameters. For that purpose, we perform a variable frequency analysis during the evolutionary process.
KeywordsDispatching Rules Genetic Programming Dynamic Dial-a-ride Problem
Unable to display preview. Download preview PDF.
- 1.Affenzeller, M., Winkler, S., Wagner, S., Beham, A.: Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications (Numerical Insights), 1st edn. Chapman & Hall (April 2009)Google Scholar
- 3.Beham, A., Kofler, M., Wagner, S., Affenzeller, M.: Agent-based simulation of dispatching rules in dynamic pickup and delivery problems. In: 2nd International Logistics and Industrial Informatics, LINDI 2009, pp. 1–6. IEEE (2009)Google Scholar
- 9.Fu, M.C., Glover, F.W., April, J.: Simulation optimization: a review, new developments, and applications. In: 2005 Proceedings of the Winter Simulation Conference, 13. p. IEEE (2005)Google Scholar
- 10.Kronberger, G.: Symbolic Regression for Knowledge Discovery – Bloat, Overfitting, and Variable Interaction Networks. No. 64 in Johannes Kepler University, Linz, Reihe C, Trauner Verlag+Buchservice GmbH (2011)Google Scholar
- 11.Laporte, G.: Recent algorithms for the dial-a-ride problem. In: Operations Research for Complex Decision Making, p. 13 (2010)Google Scholar
- 12.Larsen, A., Madsen, O., Solomon, M.: Partially dynamic vehicle routing-models and algorithms. Journal of the Operational Research Society, 637–646 (2002)Google Scholar
- 13.van Lon, R., Holvoet, T., Vanden Berghe, G., Wenseleers, T., Branke, J.: Evolutionary synthesis of multi-agent systems for dynamic dial-a-ride problems. In: Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, pp. 331–336. ACM (2012)Google Scholar
- 14.Pitzer, E., Beham, A., Affenzeller, M., Heiss, H., Vorderwinkler, M.: Production fine planning using a solution archive of priority rules. In: 2011 3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI), pp. 111–116. IEEE (2011)Google Scholar
- 16.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