A Discrete Particle Swarm Optimization Algorithm for Bi-Criteria Warehouse Location Problem

Fehmi Burcin Ozsoydan () and Tugba Sarac ()
Additional contact information
Fehmi Burcin Ozsoydan: Osmangazi University
Tugba Sarac: Osmangazi University

Istanbul University Econometrics and Statistics e-Journal, 2011, vol. 13, issue 1, 114-124

Abstract: The uncapacitated warehouse location problem (UWLP) is one of the widely studied discrete location problems, in which the nodes (customers) are connected to a number (w) of warehouses in such a way that the total cost, yields from the dissimilarities (distances) and from the fixed costs of the warehouses is minimized. Despite w is considered as fixed integer number, the UWLP is NP-hard. If the UWLP has two or more objective functions and w is an integer variable, the UWLP becomes more complex. Large size of this kind of complex problems can be solved by using heuristic algorithms or artificial intelligent techniques. It’s shown that Particle Swarm Optimization (PSO) which is one of the technique of artificial intelligent techniques, has achieved a notable success for continuous optimization, however, PSO implementations and applications for combinatorial optimization are still active research area that to the best of our knowledge fewer studies have been carried out on this topic. In this study, the bi-criteria UWLP of minimizing the total distance and total opening cost of warehouses. is presented and it’s shown that promising results are obtained.

Keywords: Warehouse Location Problem; Particle Swarm Optimization; Discrete Location Problems; Bi-criteria. (search for similar items in EconPapers)
JEL-codes: C61 C63 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://eidergisi.istanbul.edu.tr/sayi13/iueis13m7.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ist:ancoec:v:13:y:2011:i:1:p:114-124

Access Statistics for this article

Istanbul University Econometrics and Statistics e-Journal is currently edited by Kutluk Kagan Sumer

More articles in Istanbul University Econometrics and Statistics e-Journal from Department of Econometrics, Faculty of Economics, Istanbul University Contact information at EDIRC.
Bibliographic data for series maintained by Istanbul University Press Operational Team (Ertuğrul YAŞAR) ().