TY - JOUR
T1 - A new Hybrid Genetic Variable Neighborhood search heuristic for the Vehicle Routing Problem with Multiple Time Windows
AU - Belhaiza, Slim
AU - M'Hallah, Rym
AU - Brahim, Ghassen Ben
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/7/5
Y1 - 2017/7/5
N2 - The Vehicle Routing Problem (VRP) is a known optimization problems falling under the category of NP-Hard set of problems. VRP, along with its variations, continue to be extensively explored by the research community due to their large domain of application (environment, agriculture, industry, etc.) and economic impact on improving the overall performance, Quality of Services and reducing the operational cost. In this paper, we focus on VRPMTW; a variant of VRP with Multiple Time Windows constraints. We introduce a novel Hybrid Genetic Variable Neighborhood Search (HGVNS) based heuristic for the optimization of VRPMTW. The proposed framework uses genetic cross-over operators on a list of best parents and new implementations of local search operators. Computational results on benchmark data show substantial performance improvement when using the newly introduced heuristic.
AB - The Vehicle Routing Problem (VRP) is a known optimization problems falling under the category of NP-Hard set of problems. VRP, along with its variations, continue to be extensively explored by the research community due to their large domain of application (environment, agriculture, industry, etc.) and economic impact on improving the overall performance, Quality of Services and reducing the operational cost. In this paper, we focus on VRPMTW; a variant of VRP with Multiple Time Windows constraints. We introduce a novel Hybrid Genetic Variable Neighborhood Search (HGVNS) based heuristic for the optimization of VRPMTW. The proposed framework uses genetic cross-over operators on a list of best parents and new implementations of local search operators. Computational results on benchmark data show substantial performance improvement when using the newly introduced heuristic.
KW - Genetic Algorithm
KW - Variable Neighborhood Search
KW - VRP with Multiple Time Windows
UR - http://www.scopus.com/inward/record.url?scp=85027851810&partnerID=8YFLogxK
U2 - 10.1109/CEC.2017.7969457
DO - 10.1109/CEC.2017.7969457
M3 - Article
AN - SCOPUS:85027851810
SP - 1319
EP - 1326
JO - 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
JF - 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
T2 - 2017 IEEE Congress on Evolutionary Computation, CEC 2017
Y2 - 5 June 2017 through 8 June 2017
ER -