A cycle-based evolutionary algorithm for the fixed-charge capacitated multi-commodity network design problem

Paraskevopoulos, D. C., Bektaş, T., Crainic, T. G. & Potts, C. N. (2016). A cycle-based evolutionary algorithm for the fixed-charge capacitated multi-commodity network design problem. European Journal of Operational Research, 253(2), pp. 265-279. doi: 10.1016/j.ejor.2015.12.051

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Abstract

This paper presents an evolutionary algorithm for the fixed-charge multicommodity network design problem (MCNDP), which concerns routing multiple commodities from origins to destinations by designing a network through selecting arcs, with an objective of minimizing the fixed costs of the selected arcs plus the variable costs of the flows on each arc. The proposed algorithm evolves a pool of solutions using principles of scatter search, interlinked with an iterated local search as an improvement method. New cycle-based neighborhood operators are presented which enable complete or partial re-routing of multiple commodities. An efficient perturbation strategy, inspired by ejection chains, is introduced to perform local compound cycle-based moves to explore different parts of the solution space. The algorithm also allows infeasible solutions violating arc capacities while performing the "ejection cycles", and subsequently restores feasibility by systematically applying correction moves. Computational experiments on benchmark MCNDP instances show that the proposed solution method consistently produces high-quality solutions in reasonable computational times.

Publication Type: Article
Additional Information: © 2016 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Multi-commodity network design, Scatter search, Evolutionary algorithms, Ejection chains, Iterated local search
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics
Departments: Cass Business School > Faculty of Management
URI: http://openaccess.city.ac.uk/id/eprint/19844

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