Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
A tabu search procedure for multicommodity location/allocation with balancing requirements
Annals of Operations Research - Special issue on Tabu search
Network Design for Express Shipment Delivery
Computational Optimization and Applications
Multimodal Express Package Delivery: a Service Network Design Application
Transportation Science
A Simplex-Based Tabu Search Method for Capacitated Network Design
INFORMS Journal on Computing
Composite Variable Formulations for Express Shipment Service Network Design
Transportation Science
Interfaces
A two-stage stochastic programming model for transportation network protection
Computers and Operations Research
A bi-level programming for logistics network design with system-optimized flows
Information Sciences: an International Journal
Branch and Price for Service Network Design with Asset Management Constraints
Transportation Science
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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-efficient 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. Specifically, 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 efficient 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 efficient 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 is adopted for the sub-problem solution. The contribution of this paper is an efficient algorithm, along with detailed analyses of effective mechanisms which can help to increase the speed of the GLS algorithm for the SNDP.