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). 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece, 06.12.2016-09.12.2016. Piscataway, NJ, USA: Institute of Electrical and Electronic Engineers, Inc. https://doi.org/10.1109/SSCI.2016.7850084

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.