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Optimisation of transportation service network using k-node large neighbourhood search

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posted on 2023-06-09, 06:45 authored by Ruibin Bai, John R Woodward, Nachiappan SubramanianNachiappan Subramanian, John Cartlidge
The Service Network Design Problem (SNDP) is generally considered as a fundamental problem in transportation logistics. It involves the determination of an efficient transportation network and corresponding schedules. The problem is extremely challenging because of the complexity of the constraints and the scale of real-world applications. Therefore, efficient solution methods for this problem are one of the most important research topics in this field. However, current research has mainly focused on various sophisticated high-level search strategies in the form of different local search metaheuristics and their hybrids. Little attention has been paid to novel neighbourhood structures, despite the crucial role they play in the performance of the algorithm. In this research, we propose a new efficient neighbourhood structure that uses the constraints of SNDP to its advantage and more importantly appears to have better reachability than the existing ones. The effectiveness of this new neighbourhood is evaluated with a basic Tabu Search (TS) metaheuristic and a basic Guided Local Search method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs better than the previous arc-flipping neighbourhood. The performance of the TS metaheuristic based on the proposed neighbourhood is further enhanced through fast neighbourhood search heuristics and hybridisation with other approaches.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Computers & Operations Research

ISSN

0305-0548

Publisher

Elsevier

Volume

89

Page range

193-205

Department affiliated with

  • Business and Management Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2017-06-16

First Open Access (FOA) Date

2017-06-16

First Compliant Deposit (FCD) Date

2017-06-16

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