Using the maximal covering location problem to design a sustainable recycling network

Abstract Recycling networks are essential to achieve sustainability in supply chains. Moreover, the design of recycling networks commonly focuses on reducing the costs of collecting a specific amount of end-of-life products or maximizing profit. We are interested in different scenarios with a non-profit approach where given an initial budget, our goal is to design a recycling network where the economic benefits from selling products for reuse or recycle are used to increase the network capacity so we maximize the amount of collected end-of-life products. We implement classic operations research techniques to represent the decision-making process with a maximal covering facility location problem that determines the following decisions: the number and location of capacitated collection centers with a limited-service area; the flow of end-of-life products from demand centers to collection centers and then, to capacitated recycling plants; and the amount of collected products sold to the secondary market. We design a mixed-integer linear formulation for our optimization problem, which can be solved with commercial solvers in short computational times for most of the large instances considered in our experimental stage. Numerical results on a case study in Brazil show that our optimization approach is a handy tool to design a recycling network and identify recycling plants with high low-usage rates.