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dc.contributor.advisorDao Vu Truong, Son
dc.contributor.authorPham Nguyen Nhu, Ngoc
dc.date.accessioned2020-10-19T07:01:05Z
dc.date.available2020-10-19T07:01:05Z
dc.date.issued2019
dc.identifier.other022005212
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/3642
dc.description.abstractThe Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem. Because the time and complexity in finding solution grow exponentially with the size in each problem, CVRP is also identified as a NP-hard problem. Meta-heuristic algorithms are considered as an effective method to solve CVRP. There are several meta-heuristic algorithms introduced with different philosophies of intensification. This report focuses on 2 heuristic algorithms: Particle Swarm Optimization, and Grey Wolf Optimization. This study also uses K-means algorithm in clustering, which is a good way to reduce the complexity of CVRP. The comparison of computation time, accuracy and convergence is also included in this report. Keywords: Capacitated Vehicle Routing Problem, Particle Swarm Optimization, Grey Wolf Optimization, K-meansen_US
dc.language.isoen_USen_US
dc.publisherInternational University - HCMCen_US
dc.subjectCapacitated vehicle routing problemen_US
dc.titlePerformance of grey wolf optimization and particle swarm optimization combined with kmeans in capacitated vehicle routing problemen_US
dc.typeThesisen_US


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