Title: Cost optimisation of supply chain networks using Ant Colony Optimisation

Authors: P.S.S. Prasad, C. Shankhar

Addresses: Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, India. ' Department of Mechanical Engineering, Karpagam College of Engineering, Coimbatore 641032, India

Abstract: With increasing competitiveness in the business world, the focus on supply chains is receiving more attention. Therefore, the supply chain has to be made more effective by reducing unnecessary losses. These losses are caused due to production, distribution planning and improper routing of vehicles in supply chain networks. The objective of this paper is to reduce costs across the supply chain by effectively allocating distribution centres to warehouses, reducing transportation costs and inventory costs. A non-traditional optimisation tool that can effectively find good solutions to difficult combinatorial problems is Ant Colony Optimisation (ACO). ACO is a meta-heuristic that generates information about the optimisation procedure in the form of a pheromone matrix. This information can be shared and used by members of the colony. This provides a platform to manage the supply chain optimally. The ants start from the warehouse and travel to various distribution centres which are assigned to the respective warehouses for distribution. A pheromone matrix was developed based on the input information from all the ants. Constraints were imposed on the routes traversed by ants. The constraints given for ants are warehouse capacity and maximum distance to be travelled by ants.

Keywords: supply chain networks; non-traditional optimisation; transportation costs; ant colony optimisation; competitiveness; loss reduction; unnecessary losses; production factors; distribution planning; improper routing; vehicle routes; distribution centres; warehouses; inventory costs; inventories; combinatorial problems; meta-heuristics; optimisation procedures; pheromone matrix; input information; ants; ant colonies; warehouse capacities; maximum distances; SCM; supply chain management; global supply chains; globalisation; logistics systems; logistics management.

DOI: 10.1504/IJLSM.2011.041507

International Journal of Logistics Systems and Management, 2011 Vol.9 No.2, pp.218 - 228

Available online: 25 Jul 2011 *

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