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Computer Science > Neural and Evolutionary Computing

arXiv:2211.12728 (cs)
[Submitted on 23 Nov 2022]

Title:Stochastic Capacitated Arc Routing Problem

Authors:Fleury Gérard, Lacomme Philippe, Christian Prins
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Abstract:This paper deals with the Stochastic Capacitated Arc Routing Problem (SCARP), obtained by randomizing quantities on the arcs in the CARP. Optimization problems for the SCARP are characterized by decisions that are made without knowing their full consequences. For real-life problems, it is important to create solutions insensitive to variations of the quantities to collect because of the randomness of these quantities. Efficient robust solutions are required to avoid unprofitable costly moves of vehicles to the depot node. Different criteria are proposed to model the SCARP and advanced concepts of a genetic algorithm optimizing both cost and robustness are provided. The method is benchmarked on the well-known instances proposed by DeArmon, Eglese and Belenguer. The results prove it is possible to obtain robust solutions without any significant enlargement of the solution cost. This allows treating more realistic problems including industrial goals and constraints linked to variations in the quantities to be collected.
Subjects: Neural and Evolutionary Computing (cs.NE)
Report number: Research Report LIMOS/RR-05-12
Cite as: arXiv:2211.12728 [cs.NE]
  (or arXiv:2211.12728v1 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2211.12728

Submission history

From: Philippe Lacomme Dr [view email]
[v1] Wed, 23 Nov 2022 06:39:17 UTC (2,549 KB)
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