Closed-Loop Supply Chain Network Design with Flexible Capacity under Uncertain Environment

This paper incorporates flexible facility capacity and government subsidy factors into the consideration of the design of a closed-loop supply chain(CLSC) network based on an uncertain environment. Considering the minimization of economic cost and carbon emission, a multi-objective multi-period multi-product mixed integer linear programming model with fixed and flexible facility capacity is constructed respectively. The robust optimization method is applied to deal with the uncertain environment of demand, recycled product quality, and recycling rate faced by the CLSC, and the robust models under six uncertain sets are constructed respectively. For model solving, the designed algorithm uses the augmented epsilon-constraint method to handle multi-objective problems and introduces a three-stage method on top of the Benders decomposition algorithm to accelerate the efficiency of solving the main problem. Finally, through numerical cases, a CSLC with a flexible supply strategy can manage economic and environmental costs to cope with the negative impacts of an uncertain environment, while this paper verifies the effectiveness of the government subsidy strategy under different conditions and analyzes the potential limitations.