A self-adaptive bat algorithm for the truck and trailer routing problem. Issue 1 (5th March 2018)

• Record Type: Journal Article
• Authors: Wang, Chao; Zhou, Shengchuan; Gao, Yang; Liu, Chao
• Is Part Of: Engineering computations. Volume 35:Issue 1(2018)
• Page Start: 108
• Page End: 135
• Publication Date: 2018-03-05
• Subjects: Vehicle routing -- Bat algorithm -- Self-adaptive -- Truck and trailer; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-11-2016-0408
• Languages: English
• ISSNs: 0264-4401

Abstract

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.