A self-adaptive bat algorithm for the truck and trailer routing problem

Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing...

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Published inEngineering computations Vol. 35; no. 1; pp. 108 - 135
Main Authors Wang, Chao, Zhou, Shengchuan, Gao, Yang, Liu, Chao
Format Journal Article
LanguageEnglish
Published Bradford Emerald Publishing Limited 01.01.2018
Emerald Group Publishing Limited
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ISSN0264-4401
1758-7077
DOI10.1108/EC-11-2016-0408

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Abstract Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers. Design/methodology/approach The meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature. Findings Computational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms. Originality/value In this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors’ knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem.
AbstractList Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers. Design/methodology/approach The meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature. Findings Computational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms. Originality/value In this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors’ knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem.
PurposeThe purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers.Design/methodology/approachThe meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature.FindingsComputational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms.Originality/valueIn this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors’ knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem.
Author Gao, Yang
Zhou, Shengchuan
Liu, Chao
Wang, Chao
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Issue 1
Keywords Self-adaptive
Truck and trailer
Bat algorithm
Vehicle routing
Language English
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Snippet Purpose The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important...
PurposeThe purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important...
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SubjectTerms Adaptive algorithms
Algorithms
Combinatorial analysis
Computational efficiency
Computing time
Customers
Design
Heuristic
Heuristic methods
Milk
Optimization
Route planning
Tractor trailers
Trucks
Vehicle routing
Vehicles
Title A self-adaptive bat algorithm for the truck and trailer routing problem
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