Optimization Model for Integrated Municipal Solid Waste System Using Stochastic Chance-Constraint Programming under Uncertainty: A Case Study in Qazvin, Iran

Municipal solid waste management (MSW) is a factor that affects environmental pollution and the spread of diseases in cities. Therefore, an efficient MSW system results reducing cost impact by tackling processes collection, recycling, disposal. In this study, biobjective optimization model developed which aims to minimize costs facility location transportation planning emission pollutants. Furthermore, consider uncertain nature problem, demand or volume generated considered as random parameter. As result, stochastic mathematical programming with probable constraints developed. To solve validate model, ε-constraint approach has been employed. Moreover, for real-world application proposed case study implemented Qazvin, Iran. Finally, various problems are solved different levels reliability designed each them. Results show method was able achieve Pareto solutions where managers can decide choose one them based on their priorities comparison current status. revealed would be reduced increasing confidence level. made between our recently used solution approaches.