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An effective memetic algorithm for the cumulative capacitated vehicle routing problem
Authors:Sandra Ulrich Ngueveu  Christian Prins  Roberto Wolfler Calvo
Affiliation:1. Institut Charles Delaunay - LOSI, Université de Technologie de Troyes (UTT), 12, rue Marie Curie, 10000 Troyes, France;2. Laboratoire d’Informatique de l’Université Paris-Nord (LIPN) UMR 7030, 99, av. Jean-Baptiste Clément, 93430 Villetaneuse, France;1. Institut Charles Delaunay - LOSI, Université de Technologie de Troyes (UTT), BP 2060, 10010 Troyes Cedex, France;2. Institut Charles Delaunay - LOSI, Université de Technologie de Troyes (UTT), BP 2060, 10010 Troyes Cedex, France;3. Institut Charles Delaunay - LOSI, Université de Technologie de Troyes (UTT), BP 2060, 10010 Troyes Cedex, France;4. Laboratoire d''Informatique de l''Université Paris-Nord (LIPN), UMR 7030, 99 avenue Jean-Baptiste Clément, 93430 Villetaneuse, France
Abstract:The cumulative capacitated vehicle routing problem (CCVRP) is a transportation problem which occurs when the objective is to minimize the sum of arrival times at customers, instead of the classical route length, subject to vehicle capacity constraints. This type of challenges arises whenever priority is given to the satisfaction of the customer need, e.g. vital goods supply or rescue after a natural disaster. The CCVRP generalizes the NP-hard traveling repairman problem (TRP), by adding capacity constraints and a homogeneous vehicle fleet. This paper presents the first upper and lower bounding procedures for this new problem. The lower bounds are derived from CCVRP properties. Upper bounds are given by a memetic algorithm using non-trivial evaluations of cost variations in the local search. Good results are obtained not only on the CCVRP, but also on the special case of the TRP, outperforming the only TRP metaheuristic published.
Keywords:
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