Resilient Supply Chain Optimization Considering Alternative Supplier Selection and Temporary Distribution Center Location

The global supply chain is facing huge uncertainties due to potential emergencies, and the disruption of any link may threaten security chain. This paper considers a scenario in which distribution center failure occur simultaneously from point view manufacturer. A resilient optimization model developed based on combination proactive reactive defense strategies, including manufacturer’s raw material mitigation inventory, preference for temporary locations, product design changes, with objective obtaining maximum expected profit. proposed stochastic planning demand uncertainty approximated as mixed integer linear programming using Latin hypercube sampling (LHS), sample average approximation (SAA), reduction (SR) methods. In addition, an improved genetic algorithm (GA) also determine approximate optimal solution. ensures feasibility solution improves solving efficiency through specific heuristic repair strategies. Numerical experiments are conducted verify application advantages recovery approach. experimental results show that can effectively reduce cost manufacturers after disruption, approach performs well dealing related problems.