Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25533
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Authors: Bai, Ruibin
Woodward, John
Subramanian, Nachiappan
Contact Email: jrw@cs.stir.ac.uk
Title: A new fast large neighbourhood search for service network design with asset balance constraints
Citation: Bai R, Woodward J & Subramanian N (2017) A new fast large neighbourhood search for service network design with asset balance constraints In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Piscataway, NJ, USA: Institute of Electrical and Electronic Engineers, Inc.. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6.12.2016 - 9.12.2016, Athens, Greece.
Issue Date: 13-Feb-2017
Conference Name: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)
Conference Dates: 2016-12-06T00:00:00Z
Conference Location: Athens, Greece
Abstract: The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.
Status: Book Chapter: publisher version
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