Simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management

One of the most critical issues facing supply chain managers in today's globalized and highly-uncertain business environment is how to proactively deal with risks that might cause serious severances and distortions of material flows in a supply chain. This paper proposes a simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management, which proactively deals with the negative consequences of random and hazardous risk events in sourcing, production, distribution, and transportation in an integrated way. The proposed approach incorporates the production lot size of the plant, order quantity and reorder point of DC, and five response coefficients as decision variables to potential risks. The proposed approach is successfully applied to an industrial example of a consumer electronics manufacturing company. The results of the computational study show that the systematic risk management of global supply chains using the proposed approach increases the profit by 20% and 16.1% in the industrial example in comparison with passive and active risk management, respectively. In addition, a mixed strategy for the inventory management of distribution centers is suggested to improve the profits of global supply chains subject to substantial risks.