Vehicle routing problems with time windows and multiple service workers: a systematic comparison between ACO and GRASP

Gerald Senarclens de Grancy () and Marc Reimann

Central European Journal of Operations Research, 2016, vol. 24, issue 1, 29-48

Abstract: This paper systematically compares an ant colony optimization (ACO) and a greedy randomized adaptive search procedure (GRASP) metaheuristic. Both are used to solve the vehicle routing problem with time windows and multiple service workers. In order to keep the results comparable, the same route construction heuristic and local search procedures are used. It is shown that ACO clearly outperforms GRASP in the problem under study. Additionally, new globally best results for the used benchmark problems are presented. Copyright Springer-Verlag Berlin Heidelberg 2016

Keywords: Vehicle routing; Time windows; Local search; Ant colony optimization; GRASP; Metaheuristics (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10100-014-0341-z

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