Harris, Irina  ORCID: https://orcid.org/0000-0003-0622-5123, Mumford, Christine Lesley ORCID: https://orcid.org/0000-0002-4514-0272 and Naim, Mohamed Mohamed ORCID: https://orcid.org/0000-0003-3361-9400
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: | Schools > Business (Including Economics) Research Institutes & Centres > 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: | 05 Nov 2022 15:36 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/23617 |
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