Designing a new robust solid waste recycling network under uncertainty: A case study about circular economy transition

Abstract

Solid waste generation continuously puts tremendous pressure on human health, socio-economic and environmental protection, and many regions are transitioning to the circular economy using waste recycling to advance sustainable development. A more practical and integrated solid waste recycling network (SWRN) design is essential for solid waste recycling management, which can be complex and uncertain. Therefore, this paper focuses on the design of a robust SWRN that aims to optimize the construction of sorting centers (SCs) while robustly operating with waste recycling allocation. This approach often involves two main challenges related to the uncertainty of unknown distribution information and the bi-level structure of decision making. To address these challenges, we first present two pairs of uncertainty sets to capture the separation rate and transportation cost in the case of free distribution information. Then, we develop a bi-level framework that integrates SC construction locations and waste operation allocation. For this purpose, a globalized robust optimization bi-level model is developed and reformulated into a mixed integer linear programming. We apply this methodology to the case of Baoding, China to demonstrate its validity. The main numerical achievements show that: (1) the proposed model can hedge the uncertainty in the separation rate and transportation cost with a small price of robustness and provide a robust recovery scheme; (2) the average operating cost of our model for a single period is approximately 19.4% lower than that of the classical robust model; and (3) by adjusting several parameters based on the preferences of waste recycling managers, a balance between operating costs and robustness can be achieved. Finally, some managerial insights are obtained to assist waste recycling managers in solid waste recycling management transition to the circular economy.