DocumentCode :
1642269
Title :
The multi-objective uncapacitated facility location problem for green logistics
Author :
Harris, Irina ; Mumford, Christine ; Naim, Mohamed
Author_Institution :
Dept. of Comput. Sci., Cardiff Univ., Cardiff
fYear :
2009
Firstpage :
2732
Lastpage :
2739
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.
Keywords :
environmental factors; facility location; genetic algorithms; minimisation; sorting; warehousing; cost minimization; distribution centres; distribution network; economic cost; environmental impact; environmental transport cost; fast nondominated sorting genetic algorithm; green logistics; human decision maker; logistics operators; multiobjective uncapacitated facility location problem; single-objective optimization; warehouses; Costs; Environmental economics; Genetic algorithms; Logistics; Optimization methods; Profitability; Recycling; Sorting; Strategic planning; Transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
Type :
conf
DOI :
10.1109/CEC.2009.4983285
Filename :
4983285
Link To Document :
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