Generalization of the MOACS algorithm for Many Objectives: An application to motorcycle distribution

dc.creatorBarán,Benjamín
dc.creatorLaufer,Melissa
dc.date2015-08-01
dc.date.accessioned2023-09-25T18:35:23Z
dc.date.available2023-09-25T18:35:23Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002015000200009
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838512
dc.descriptionTo solve many-objective routing problems, this paper generalizes the Multi-Objective Ant Colony System (MOACS) algorithm, a well-known Multi-Objective Ant Colony Optimization (MOACO) metaheuristic proposed in 2003. This Generalized MOACS algorithm is used to solve a Split-Delivery/Mixed-Fleet Vehicle Routing Problem (SD/MF-VRP) under different constraints, resulting from the mathematical modeling of a logistic problem: the distribution of motorcycles by a Paraguayan factory, considering several objective functions as: (1) total distribution cost, (2) total traveled distance, (3) total traveled time, and (4) unsatisfied demand. Experimental results using the proposed algorithm in weekly operations of the motorcycle factory prove the advantages of using the proposed algorithm, facilitating the work of the logistic planner, reducing the distribution cost and minimizing the time needed to satisfy customers.
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.18 n.2 2015
dc.subjectMultiobjective Optimization
dc.subjectMany-Objective Optimization
dc.subjectVehicle Routing Problem
dc.subjectAnt Colony Optimization
dc.subjectDistribution
dc.titleGeneralization of the MOACS algorithm for Many Objectives: An application to motorcycle distribution
dc.typeinfo:eu-repo/semantics/article


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