A supply chain is a complex network which\ninvolves the products, services and information flows\nbetween suppliers and customers. A typical supply chain\nis composed of different levels, hence, there is a need\nto optimize the supply chain by finding the optimum\nconfiguration of the network in order to get a good\ncompromise between the multi-objectives such as cost\nminimization and lead-time minimization. There are\nseveral multi-objective optimization methods which have\nbeen applied to find the optimum solutions set based\non the Pareto front line. In this study, a swarm-based\noptimization method, namely, the bees algorithm is\nproposed in dealing with the multi-objective supply chain\nmodel to find the optimum configuration of a given supply\nchain problem which minimizes the total cost and the\ntotal lead-time. The supply chain problem utilized in this\nstudy is taken from literature and several experiments\nhave been conducted in order to show the performance\nof the proposed model; in addition, the results have\nbeen compared to those achieved by the ant colony\noptimization method. The results show that the proposed\nbees algorithm is able to achieve better Pareto solutions for\nthe supply chain problem.
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