Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem

One of the best heuristic algorithms for solving the capacitated vehicle routing problem is a hybrid genetic search. A critical component of the search is a splitting procedure, where a solution encoded as a giant tour of nodes is optimally split into vehicle routes using dynamic programming. Howeve...

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Main Author: Lars Magnus Hvattum
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Algorithms
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Online Access:https://www.mdpi.com/1999-4893/18/3/165
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author Lars Magnus Hvattum
author_facet Lars Magnus Hvattum
author_sort Lars Magnus Hvattum
collection DOAJ
description One of the best heuristic algorithms for solving the capacitated vehicle routing problem is a hybrid genetic search. A critical component of the search is a splitting procedure, where a solution encoded as a giant tour of nodes is optimally split into vehicle routes using dynamic programming. However, the current state-of-the-art implementation of the splitting procedure assumes that the start of the giant tour is fixed as a part of the encoded solution. This paper examines whether the fixed starting point is a significant drawback. Results indicate that simple adjustments of the starting point for the splitting procedure can improve the performance of the genetic search, as measured by the average primal gaps of the final solutions obtained, by 3.9%.
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spelling doaj-art-dcc979ef47d8413c9defb429bae047402025-08-20T02:11:12ZengMDPI AGAlgorithms1999-48932025-03-0118316510.3390/a18030165Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing ProblemLars Magnus Hvattum0Faculty of Logistics, Molde University College, 6402 Molde, NorwayOne of the best heuristic algorithms for solving the capacitated vehicle routing problem is a hybrid genetic search. A critical component of the search is a splitting procedure, where a solution encoded as a giant tour of nodes is optimally split into vehicle routes using dynamic programming. However, the current state-of-the-art implementation of the splitting procedure assumes that the start of the giant tour is fixed as a part of the encoded solution. This paper examines whether the fixed starting point is a significant drawback. Results indicate that simple adjustments of the starting point for the splitting procedure can improve the performance of the genetic search, as measured by the average primal gaps of the final solutions obtained, by 3.9%.https://www.mdpi.com/1999-4893/18/3/165vehicle routing problemgenetic algorithmopen sourcegenetic operator
spellingShingle Lars Magnus Hvattum
Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
Algorithms
vehicle routing problem
genetic algorithm
open source
genetic operator
title Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
title_full Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
title_fullStr Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
title_full_unstemmed Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
title_short Where to Split in Hybrid Genetic Search for the Capacitated Vehicle Routing Problem
title_sort where to split in hybrid genetic search for the capacitated vehicle routing problem
topic vehicle routing problem
genetic algorithm
open source
genetic operator
url https://www.mdpi.com/1999-4893/18/3/165
work_keys_str_mv AT larsmagnushvattum wheretosplitinhybridgeneticsearchforthecapacitatedvehicleroutingproblem