Title: Production and distribution scheduling of Supply Chain structure using intelligent Particle Swarm Optimisation algorithm

Authors: Rajeshwar S. Kadadevaramath, K.M. Mohanasundaram, K. Rameshkumar, B. Chandrashekhar

Addresses: Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India; Department of Mechanical Engineering, Amrita School of Engineering, Ettimadai, Coimbatore 641105, Tamil Nadu, India. ' Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India; Department of Mechanical Engineering, Amrita School of Engineering, Ettimadai, Coimbatore 641105, Tamil Nadu, India. ' Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India; Department of Mechanical Engineering, Amrita School of Engineering, Ettimadai, Coimbatore 641105, Tamil Nadu, India. ' Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, Tamil Nadu, India; Department of Mechanical Engineering, Amrita School of Engineering, Ettimadai, Coimbatore 641105, Tamil Nadu, India

Abstract: In today|s global market, managing the entire Supply Chain (SC) becomes a key factor for the successful business and businesses have to be more adaptive to change. World class organisations now realise that non-integrated manufacturing processes, non-integrated distribution processes and poor relationship with suppliers and customers are inadequate for their success. Recently, however, there has been increasing attention placed on the performance, design and analysis of the SC as a whole. This paper specifically deals with the modelling and optimisation of a four-stage SC using the Particle Swarm Optimisation (PSO) algorithm and the problem was solved for optimal distribution of components and products made by them using PSO algorithm. And it was found that the PSO algorithm has been successfully applied to solve problems in SC network optimisation and gives quality results.

Keywords: intelligent PSO; particle swarm optimisation; probabilistic demand; supply chain management; SCM; production scheduling; distribution scheduling.

DOI: 10.1504/IJISTA.2009.024262

International Journal of Intelligent Systems Technologies and Applications, 2009 Vol.6 No.3/4, pp.249 - 268

Available online: 30 Mar 2009 *

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