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Improving Robustness of Solutions to Arc Routing Problem

Abstract : This paper considers the stochastic capacitated arc routing problem (SCARP), obtained by taking random demands in the CARP. For real-world problems, it is important to create solutions that are insensitive to changes in demand, because these quantities are not deterministic but randomly distributed. This paper provides the basic concept of a new technique to compute such solutions, based upon the best method published for CARP: a hybrid genetic algorithm (HGA). The simulation analysis was achieved with the well-known DeArmon's, Eglese's and Belenguer's instances. This intensive evaluation process was carried out with 1000 replications providing high-quality statistical data. The results obtained prove that there is a great interest to optimize not only the solution cost but also the robustness of solutions. This work is a step forward to treat more realistic problems including industrial goals and constraints linked to demand variations.
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Contributor : Wahiba Ramdane Cherif Connect in order to contact the contributor
Submitted on : Friday, September 23, 2005 - 4:22:57 PM
Last modification on : Sunday, June 26, 2022 - 1:34:57 AM



Gérard Fleury, Philippe Ph. Lacomme, Christian Prins, Wahiba Ramdane-Cherif. Improving Robustness of Solutions to Arc Routing Problem. Journal of the Operational Research Society, 2005, 56 (5), pp.526-538. ⟨10.1057/palgrave.jors.2601822⟩. ⟨inria-00000300⟩



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