Cost optimisation of supply chain networks using Ant Colony Optimisation

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.