A Cooperative Multi Colony Ant Optimization Based Approach to Efficiently Allocate Customers to Multiple Distribution Centers in a Supply Chain Network
With the rapid change of world economy, firms need to de ploy alternative methodologies to improve the responsiveness of supply chain. The present work aims to minimize the workload disparities among various distribution centres with an aim to minimize the total shipping cost. In general, this problem is characterized by its combinatorial nature and complex allocation criterion that makes its computationally intractable. In order to optimally/near optimally resolve the balanced allocation problem, an evolutionary Cooperative Multi Colony Ant Optimization (CMCAO) has been developed. This algorithm takes its gov erning traits from the traditional Ant Colony optimization (ACO). The proposed algorithm is marked by the cooperation among “sister ants” that makes it compatible to the problems pertaining to multiple dimensions. Robustness of the proposed algorithm is authenticated by com paring with GA based strategy and the efficiency of the algorithm is validated by ANOVA.
KeywordsSupply chain Balanced allocation Cooperative Multi Colony Ants ANOVA
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