In an effort to composite an optimal supply chain, this study has introduced an agent-based negotiation model as a method for assigning a lot of orders to a large number of participants. As a resources allocation mechanism to form strategic cooperation based on information sharing between supply chain members, this agent negotiation model provides such functions as bidding, scheduling, and coordination, allowing all participants to make a profit, and accomplishing a Pareto-optimum solution from the viewpoint of the whole supply chain. SET model-based scheduling takes into consideration both early (earliness) production costs and late (tardiness) production costs, along with the competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under a dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.
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