Bi-objective Optimization of a Reconfigurable Supply Chain Using a Self-organizing Migration Algorithm

In this paper, two objective functions related to supply chain performance are considered for optimization during several demand periods. Due to fast and dynamic demand variations in recent times, the supply chains for outsourced components also need agility and quick reconfiguration to adapt to these challenges. For a known demand scenario, the manufacturer must select the optimum combination of suppliers to minimize the total cost of supplies as well as the transportation cost. The two objective functions developed in this model represent the minimization of the total cost of supplies including transportation and maximization of reliability of the set of suppliers. As the two objectives may have trade-offs in many instances, a set of Pareto optimal non-dominated solutions is searched using an evolutionary algorithm called self-organizing migration algorithm or SOMA. A case study on the supply chain of a laptop computer manufacturer is selected from the literature to illustrate the implementation of algorithm to real industrial problems.

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