Authors: S. Kumanan, S. Prasanna Venkatesan, J. Prasanna Kumar
Addresses: Department of Production Engineering, National Institute of Technology, Tiruchirappalli, TamilNadu, India. ' Department of Production Engineering, National Institute of Technology, Tiruchirappalli, TamilNadu, India. ' Cognizant Technology Solutions, Chennai, TamilNadu, India
Abstract: Fierce market competition is making companies move from their traditional business strategies towards integrated strategic alliances. In order to integrate and manage their business processes like procurement, inventory, manufacturing, logistics and sales, a new technological and quantitative tool is needed. In this paper, a supply chain logistics network model is developed with the objective of minimising the total cost of production and distribution. The Genetic Algorithm (GA) and Particle Swarm (PS) search techniques are proposed for optimising the supply chain logistics network. The computational results of these algorithms are validated with the results obtained using Excel|s Solver Optimizer.
Keywords: supply chain management; SCM; logistics networks; non-traditional optimisation; genetic algorithms; GA; particle swarms; supply chain optimisation; network modelling; production costs; distribution costs; cost minimisation; random search.
International Journal of Logistics Systems and Management, 2007 Vol.3 No.2, pp.252 - 266
Published online: 24 Dec 2006 *Full-text access for editors Access for subscribers Purchase this article Comment on this article