Mixed-integer linear programming models for the paint waste management problem

Hazardous wastes have significant negative impacts on environment and people, which make their management a prominent task. A general hazardous waste reverse logistics network consists of sources, collection centers, treatment centers, processing/recycling facilities, and disposal facilities. We study a reverse logistics network specifically for household hazardous wastes and examine its difference from a non-hazardous and industrial waste network. We consider multiobjective mixed-integer deterministic and stochastic mathematical models that are designed to answer the following questions: which facilities or centers should be opened, which routes should be utilized, and how much waste should be transported to each location in order to minimize the transportation cost, transportation/site risk, and to maximize household convenience for the purpose of participation increase at collection stage. Specifically, we propose an optimization framework for the management of hazardous household wastes, and consider the waste paint network in the City of Toronto, Ontario, Canada as a test bed for our analysis. Finally, we provide easy-to-interpret visualization tools for the problem, which help interpreting the model outcomes and identifying policy insights.