DocumentCode :
2921417
Title :
The multi-objective capacitated facility location problem for green logistics
Author :
Xifeng Tang ; Ji Zhang
Author_Institution :
Sch. of Civil & Transp. Eng., Hohai Univ., Nanjing, China
fYear :
2015
fDate :
20-22 May 2015
Firstpage :
163
Lastpage :
168
Abstract :
Traditionally, the capacitated facility location problem (CFLP), which builds the basis for various location models in logistics network design, is treated as a single objective optimization problem, and focuses on minimum economic cost. Recent concerns regarding environmental pollution and commercial competition, however, are shifting the focus of modeling to incorporate not only service objectives but also environmental objectives. This paper presents a multi-objective CFLP model to trade off among economic cost, service level, and environmental impact. A hybrid evolutionary approach, which combines the fast Non-dominated Sorting Genetic Algorithm (NSGA-II) and the greedy algorithm, is employed to generate the Pareto-optimal solutions. Test results show that the proposed method can offer decision makers an informed choice of compromise solutions and is an effective toolkit can be used in facility location for green logistics.
Keywords :
Pareto optimisation; environmental factors; facility location; genetic algorithms; logistics; NSGA-ll; Pareto-optimal solutions; commercial competition; economic cost; environmental impact; environmental pollution; greedy algorithm; green logistics; hybrid evolutionary approach; location models; logistics network design; minimum economic cost; multiobjective capacitated facility location problem; nondominated sorting genetic algorithm; service level; single objective optimization problem; IEL; Manganese; Resource management; facility location prolem; genetic algorithm; green logistics; multi-objective optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Logistics and Transport (ICALT), 2015 4th International Conference on
Conference_Location :
Valenciennes
Type :
conf
DOI :
10.1109/ICAdLT.2015.7136594
Filename :
7136594
Link To Document :
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