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A Practical Approach for Robust and Flexible Vehicle Routing Using Metaheuristics and Monte Carlo Sampling

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Journal of Mathematical Modelling and Algorithms

Abstract

In this paper, we investigate how robust and flexible solutions of a number of stochastic variants of the capacitated vehicle routing problem can be obtained. To this end, we develop and discuss a method that combines a sampling based approach to estimate the robustness or flexibility of a solution with a metaheuristic optimization technique. This combination allows us to solve larger problems with more complex stochastic structures than traditional methods based on stochastic programming. It is also more flexible in the sense that adaptation of the approach to more complex problems can be easily done. We explicitly recognize the fact that the decision maker’s risk preference should be taken into account when choosing a robust or flexible solution and show how this can be done using our approach.

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Authors and Affiliations

  1. Faculty of Applied Economics, Universiteit Antwerpen, Prinsstraat 13, 2000, Antwerp, Belgium

    Kenneth Sörensen

  2. Lab-STICC - UEB, Université de Bretagne-Sud, Centre de Recherche, BP 92116, F-56321, Lorient, France

    Marc Sevaux

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  1. Kenneth Sörensen
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  2. Marc Sevaux
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Correspondence to Marc Sevaux.

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Sörensen, K., Sevaux, M. A Practical Approach for Robust and Flexible Vehicle Routing Using Metaheuristics and Monte Carlo Sampling. J Math Model Algor 8, 387–407 (2009). https://doi.org/10.1007/s10852-009-9113-5

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  • DOI: https://doi.org/10.1007/s10852-009-9113-5

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