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An evolutionary bi-objective approach to the capacitated facility location problem with cost and CO2 emissions

Harris, Irina, Mumford, Christine Lesley and Naim, Mohamed Mohamed 2011. An evolutionary bi-objective approach to the capacitated facility location problem with cost and CO2 emissions. Presented at: Genetic and Evolutionary Computation Conference (GECCO) 2011, Dublin, Ireland, 12-16 July 2011. Published in: Krasnogor, N. ed. GECCO '11 Proceedings of the 13th annual conference on Genetic and evolutionary computation. New York, NY: ACM, pp. 697-704. 10.1145/2001576.2001672

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Abstract

It is strategically important to design efficient and environmentally friendly distribution networks. In this paper we propose a new methodology for solving the capacitated facility location problem (CFLP) based on combining an evolutionary multi-objective algorithm with Lagrangian Relaxation for modelling large problem instances where financial costs and CO_2 emissions are considered simultaneously. Two levels of decision making are required: 1) which facilities to open from a set of potential sites, and 2) which customers to assign to which open facilities without violating their capacity. We choose SEAMO2 (Simple Evolutionary Multi-objective Optimization 2) as our multi-objective evolutionary algorithm to determine which facilities to open, because of its fast execution speed. For the allocation of customers to open facilities we use a Lagrangian Relaxation technique. We test our approach on large problem instances with realistic qualities, and validate solution quality by comparison with extreme solutions obtained using CPLEX.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HE Transportation and Communications
Uncontrolled Keywords: Logistics; Operations management
Publisher: ACM
ISBN: 9781450305570
Related URLs:
Last Modified: 06 Oct 2019 03:22
URI: http://orca.cf.ac.uk/id/eprint/23617

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