PARETO ANT COLONY OPTIMISATION : A METAHEURISTIC APPROACH TO SUPPLY CHAIN DESIGN

This paper proposes a new approach to determining the supply chain (SC) design for a product comprising different subassemblies. There might be multiple suppliers that could supply the same components as well as many manufacturers that could assemble the product. Each of these options is differentiated by its lead time and cost. Given all the possible options the configuration problem is to select the options that minimise the total cost while keeping the total lead time within the orders’ due date This work introduces Pareto Ant Colony Optimisation as an especially effective meta-heuristic for solving the problem of SC Design. A number of ant colonies generate a Pareto Optimal Set of SC Designs in which only the non dominated SC designs are allowed to deposit pheromones over the time and cost pheromone matrices. An experimental example is used to test the algorithm and show the benefits of utilising two pheromones matrices and multiple ant colonies in SC optimisation problem.

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