Closed-loop supply chain network design for hazardous products with uncertain demands and returns

The extensive use of hazardous products has resulted in quickly increasing on hazardous wastes. Due to the rising environmental pressure and economic benefit, the reverse supply chain design for hazardous products is becoming increasingly important and urgent. In this paper, we consider the closed-loop supply chain network design for hazardous products (HP-CLSCND), including both forward supply chain and reverse supply chain. The uncertainty inherent in closed-loop supply chain network will significantly influence the overall performance of the closed-loop supply chain network design. This paper focuses on the HP-CLSCND problem with uncertain demands and returns, and a two-stage stochastic programming model (scenario-based) is proposed, in which a risk restriction constraint and reward-penalty mechanism are simultaneously considered. Two solution approaches, parallel enumeration method (PEM) and genetic algorithm (GA) are designed to solve the proposed model. The PEM is an exact solution approach and can rapidly obtain the global optimal solution of the proposed model by utilizing multiply processors. Finally, an application example is provided to demonstrate the applicability of the proposed model and two solution approaches. The performance of PEM is evaluated by speedup radio. In addition, the sensitivity analyses about maximum acceptable risk and reward-penalty intensity are conducted, and some management insights for the government are obtained.