Posted: July 1st, 2014

Tabu assisted guided local search approaches for freight service network design

Tabu assisted guided local search approaches for freight service network design
Ruibin Baia,*, Graham Kendallb , Rong Qub , Jason Atkinb
of Computer Science, University of Nottingham Ningbo China. Tel.: +86-574-88180278, Fax: +86-574-88180125 b School of Computer Science, University of Nottingham, Nottingham, UK.
a Division

Abstract The service network design problem (SNDP) is a core problem in freight transportation. It involves the determination of the most cost-effective transportation network and the characteristics of the corresponding services, subject to various constraints. The scale of the problem in real-world applications is usually very large, especially when the network contains both the geographical information and the temporal constraints which are necessary for modelling multiple service-classes and dynamic events. The development of time-ef?cient algorithms for this problem is, therefore, crucial for successful real-world applications. Earlier research indicated that guided local search (GLS) was a promising solution method for this problem. One of the advantages of GLS is that it makes use of both the information collected during the search as well as any special structures which are present in solutions. Building upon earlier research, this paper carries out in-depth investigations into several mechanisms that could potentially speed up the GLS algorithm for the SNDP. Speci?cally, the mechanisms that we have looked at in this paper include a tabu list (as used by tabu search), short-term memory, and an aspiration criterion. An ef?cient hybrid algorithm for the SNDP is then proposed, based upon the results of these experiments. The algorithm combines a tabu list within a multi-start GLS approach, with an ef?cient feasibility-repairing heuristic. Experimental tests on a set of 24 well-known service network design benchmark instances have shown that the proposed algorithm is superior to a previously proposed tabu search method, reducing the computation time by over a third. In addition, we also show that far better results can be obtained when a faster linear program solver
author Email addresses: [email protected] (Ruibin Bai), [email protected] (Graham Kendall), [email protected] (Rong Qu), [email protected] (Jason Atkin)

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