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The multi-objective uncapacitated facility location problem for green logistics

Harris, Irina, Mumford, Christine Lesley and Naim, Mohamed Mohamed 2009. The multi-objective uncapacitated facility location problem for green logistics. Presented at: IEEE Congress on Evolutionary Computation, 2009 (CEC '09), Trondheim, Norway, 18-21 May 2009. Proceedings of the IEEE Congress on Evolutionary Computation, 2009 (CEC '09). Los Alamitos, CA: IEEE, pp. 2732-2739. 10.1109/CEC.2009.4983285

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Abstract

Traditionally, the uncapacitated facility location problem (UFLP) is solved as a single-objective optimization exercise, and focuses on minimizing the cost of operating a distribution network. This paper presents an exploratory study in which the environmental impact is modelled as a separate objective to the economic cost. We assume that the environmental cost of transport is large in comparison to the impact involved in operating distribution centres or warehouses (in terms of CO2 emissions, for example). We further conjecture that the whole impact on the environment is not fully reflected in the costs incurred by logistics operators. Based on these ideas, we investigate a number of ldquowhat if ?rdquo scenarios, using a Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II), to provide sets of non-dominated solutions to some test instances. The analysis is conducted on both two-objective (economic cost versus environmental impact) and three objective (economic cost, environmental impact and uncovered demand) models. Initial results are promising, indicating that this approach could indeed be used to provide informed choices to a human decision maker.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Computer Science & Informatics
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: H Social Sciences > HD Industries. Land use. Labor
T Technology > TD Environmental technology. Sanitary engineering
Publisher: IEEE
ISBN: 9781424429585
Last Modified: 11 Jan 2018 20:48
URI: http://orca.cf.ac.uk/id/eprint/37329

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