Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain

Driven by the supply chain, suppliers, manufacturers and warehouses are working more closely together for improving service quality. However, tremendous cost may incur in the supply chain if transportation is not planned properly and efficiently, which frustrates enterprises in the intense market. I...

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Autores principales:	Yuanhang Qi, Yanguang Cai
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	supply chain transportation systems artificial intelligence intelligent algorithm vehicle routing bat algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/219cf1aa51a44d85a215a27dd5388a7d
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spelling	oai:doaj.org-article:219cf1aa51a44d85a215a27dd5388a7d2021-11-11T15:09:55ZHybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain10.3390/app1121101012076-3417https://doaj.org/article/219cf1aa51a44d85a215a27dd5388a7d2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10101https://doaj.org/toc/2076-3417Driven by the supply chain, suppliers, manufacturers and warehouses are working more closely together for improving service quality. However, tremendous cost may incur in the supply chain if transportation is not planned properly and efficiently, which frustrates enterprises in the intense market. In this paper, we present a model of vehicle routing problem in complex supply chain (VRPCSC) and propose an intelligent algorithm called hybrid chaotic discrete bat algorithm with variable neighborhood search for minimizing the purchase cost of materials, processing cost, and delivery cost along the path from suppliers, to manufacturers and warehouses in the vehicle routing problem. Based on the principles of bat algorithm, a discrete chaotic initialization strategy (DCIS) and a variable neighborhood search (VNS) are adopted to enhance the convergence capacity. Finally, two sets of experiments are conducted, which show that the proposed algorithm can solve the VRPCSC effectively.Yuanhang QiYanguang CaiMDPI AGarticlesupply chaintransportation systemsartificial intelligenceintelligent algorithmvehicle routingbat algorithmTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10101, p 10101 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	supply chain transportation systems artificial intelligence intelligent algorithm vehicle routing bat algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	supply chain transportation systems artificial intelligence intelligent algorithm vehicle routing bat algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Yuanhang Qi Yanguang Cai Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
description	Driven by the supply chain, suppliers, manufacturers and warehouses are working more closely together for improving service quality. However, tremendous cost may incur in the supply chain if transportation is not planned properly and efficiently, which frustrates enterprises in the intense market. In this paper, we present a model of vehicle routing problem in complex supply chain (VRPCSC) and propose an intelligent algorithm called hybrid chaotic discrete bat algorithm with variable neighborhood search for minimizing the purchase cost of materials, processing cost, and delivery cost along the path from suppliers, to manufacturers and warehouses in the vehicle routing problem. Based on the principles of bat algorithm, a discrete chaotic initialization strategy (DCIS) and a variable neighborhood search (VNS) are adopted to enhance the convergence capacity. Finally, two sets of experiments are conducted, which show that the proposed algorithm can solve the VRPCSC effectively.
format	article
author	Yuanhang Qi Yanguang Cai
author_facet	Yuanhang Qi Yanguang Cai
author_sort	Yuanhang Qi
title	Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
title_short	Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
title_full	Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
title_fullStr	Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
title_full_unstemmed	Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain
title_sort	hybrid chaotic discrete bat algorithm with variable neighborhood search for vehicle routing problem in complex supply chain
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/219cf1aa51a44d85a215a27dd5388a7d
work_keys_str_mv	AT yuanhangqi hybridchaoticdiscretebatalgorithmwithvariableneighborhoodsearchforvehicleroutingproblemincomplexsupplychain AT yanguangcai hybridchaoticdiscretebatalgorithmwithvariableneighborhoodsearchforvehicleroutingproblemincomplexsupplychain
_version_	1718437109520400384

Hybrid Chaotic Discrete Bat Algorithm with Variable Neighborhood Search for Vehicle Routing Problem in Complex Supply Chain

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