Bi-criteria allocation of customers to warehouses using a particle swarm optimisation

S. Prasanna Venkatesan and S. Kumanan

International Journal of Operational Research, 2010, vol. 9, issue 1, 65-81

Abstract: Success of a firm largely depends on its supply chain decisions. Minimising cost and maximising service level are the contending objectives in strategic supply chain design. Researchers have been attempting to evolve an effective and efficient solution procedure for multi-objective supply chain models. In this paper, a multi-objective particle swarm optimisation (MOPSO) algorithm is proposed for bi-criteria allocation of customers to multiple warehouses. The proposed algorithm is developed in Matlab platform and tested. The results show that the proposed approach is capable of producing high-quality Pareto-optimal solutions.

Keywords: bi-criteria allocation; multi-objective optimisation; Pareto optimality; PSO; particle swarm optimisation; supply chain management; SCM; supply chain design; modelling; multiple warehouses; costs; service levels. (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=34361 (text/html)
Access to full text is restricted to subscribers.

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:ids:ijores:v:9:y:2010:i:1:p:65-81

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().