Optimizing e-waste recycling networks under uncertain environment: a fourth-party logistics perspective

Efficient E-waste recycling is key for electronic product manufacturing companies to achieve resource optimization and sustainable development. However, market fluctuations and the uncertainty of consumer behavior make the demand for E-waste recycling difficult to predict, presenting challenges for the design and management of recycling networks. This paper investigates the reverse logistics network design problem for E-waste under uncertain recycling demand from the perspective of 4PL innovation. Multiple 3PLs and temporary outsourcing service models are incorporated to address the uncertainty of recycling demand. A two-stage stochastic optimization model is introduced to reduce overall expenses. To improve solving efficiency, a new LHS-SAA algorithm is proposed. The model and method's effectiveness is shown through a real case study of a household appliance recycling company in northern Turkey. The comparative analysis shows that the LHS-SAA algorithm outperforms CPLEX. For the company, the 4PL operational model is more suitable for constructing the corresponding recycling network. Compared to the traditional supply chain network, the 4PL network can reduce overall costs through the collaborative cooperation of 3PLs. In addition, the results of the parameter sensitivity analysis show that the unit penalty cost, unit outsourcing cost, and minimum recycling ratio have a complex interdependent relationship in their effects on the results. The magnitude of the unit penalty cost for uncollected items has a decisive impact on the decision outcomes. When the penalty cost is low, the company can determine the scale of the 4PL network based on the minimum recycling ratio. As the minimum recycling ratio and unit outsourcing cost increase, the company should prepare more funds to build the 4PL recycling network. As the unit penalty cost increases, the scale of the 4PL network is solely dependent on the unit outsourcing cost, regardless of the value of the minimum recycling ratio.