Heuristic to solve bi-objective allocation problem in distribution logistics Online publication date: Wed, 10-Jun-2009
by R.A. Malairajan, K. Ganesh, S.C. Lenny Koh
International Journal of Logistics Economics and Globalisation (IJLEG), Vol. 2, No. 1, 2009
Abstract: Generalised assignment problem (GAP) is a well-known non-deterministic polynomial (NP) hard combinatorial optimisation problem to find the minimum cost during assignment of jobs to agents so that each job is assigned exactly once and agents are not overloaded. In this research, we look at the GAP from a bi-objective point of view to accommodate some real world situations. The application of BGAP for a typical practical supply chain problem of allocating a set of retailers to multiple distributors possessing different capacities with two specific performance objectives such as travel distance and travel time is considered. We propose a simulated annealing for an intensive search to find the Pareto optimal solutions to solve BGAP in a shorter period of time. Extensive computational experiments are carried out to evaluate the performance of the proposed method. Trials on benchmark data-sets and on a large number of test-problems have yielded encouraging results.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Logistics Economics and Globalisation (IJLEG):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook