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An improved hybrid genetic search with data mining for the CVRP.

Authors :
Maia, Marcelo Rodrigues de Holanda
Plastino, Alexandre
Souza, Uéverton dos Santos
Source :
Networks; Jun2024, Vol. 83 Issue 4, p692-711, 20p
Publication Year :
2024

Abstract

The hybrid genetic search (HGS) metaheuristic has produced outstanding results for several variants of the vehicle routing problem. A recent implementation of HGS specialized to the capacitated vehicle routing problem (CVRP) is a state‐of‐the‐art method for this variant. This paper proposes an improved HGS for the CVRP obtained by incorporating a new solution generation method into its (re‐)initialization process to guide the search more efficiently and effectively. The solution generation method introduced in this work combines an approach based on frequent patterns extracted from good solutions by a data mining process and a randomized version of the Clarke and Wright savings heuristic. As observed in our experimental comparison, the proposed method significantly outperforms the original algorithm regarding the final gap to the best known solutions and the primal integral. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00283045
Volume :
83
Issue :
4
Database :
Complementary Index
Journal :
Networks
Publication Type :
Academic Journal
Accession number :
176636114
Full Text :
https://doi.org/10.1002/net.22213