Bi‐objective optimization of distribution scheduling using MOPSO optimizer
Abstract
Purpose
The paper aims at the bi‐objective optimization of a two‐echelon distribution network model for facility location and capacity allocation where in a set of customer locations with demands and a set of candidate facility locations will be known in advance. The problem is to find the locations of the facilities and the shipment pattern between the facilities and the distribution centers (DCs) to minimize the combined facility location and shipment costs subject to a requirement that maximum customer demands be met.
Design/methodology/approach
To optimize the two objectives simultaneously, the location and distribution two‐echelon network model is mathematically represented in this paper considering the associated constraints, capacity, production and shipment costs and solved using hybrid multi‐objective particle swarm optimization (MOPSO) algorithm.
Findings
This paper shows that the heuristic based hybrid MOPSO algorithm can be used as an optimizer for characterizing the Pareto optimal front by computing well‐distributed non‐dominated solutions. These aolutions represent trade‐off solutions out of which an appropriate solution can be chosen according to industrial requirement.
Originality/value
Very few applications of hybrid MOPSO are mentioned in literature in the area of supply chain management. This paper addresses one of such applications.
Keywords
Citation
Latha Shankar, B., Basavarajappa, S. and Kadadevaramath, R.S. (2012), "Bi‐objective optimization of distribution scheduling using MOPSO optimizer", Journal of Modelling in Management, Vol. 7 No. 3, pp. 304-327. https://doi.org/10.1108/17465661211283296
Publisher
:Emerald Group Publishing Limited
Copyright © 2012, Emerald Group Publishing Limited