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

Bai, Ruibin, Woodward, John R, Subramanian, Nachiappan and Cartlidge, John (2017) Optimisation of transportation service network using k-node large neighbourhood search. Computers & Operations Research. ISSN 0305-0548

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Abstract

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.

Item Type: Article
Schools and Departments: School of Business, Management and Economics > Business and Management
Depositing User: Nachiappan Subramanian
Date Deposited: 16 Jun 2017 12:58
Last Modified: 01 Jul 2017 15:26
URI: http://sro.sussex.ac.uk/id/eprint/68662

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