Integrated Municipal Solid Waste Management under uncertainty: A tri-echelon city logistics and transportation context

Abstract The growing challenge of Municipal Solid Waste Management in mega-cities calls for development of practical decision-making support tools to assist authorities in City Logistics and Urban Planning. This study aims to optimize the logistics network and transportation system of ISWM where the complete chain of MSW/residue is formulated as a tri-echelon ISWM logistics network. Assuming various levels of complexity of a realistic ISWM system, a Mixed-Integer Linear Programming (MILP) model is developed to formulate the ISWM system in the framework of the Fleet Size and Mix Vehicle Routing Problem with Time Windows. Addressing uncertainty in ratios of MSW generation, a two-stage stochastic optimization approach is proposed to effectively support the cost-effective ISWM transportation system by determining the optimal fleet size and decomposition, vehicles routes and capacity-allocation to the system components. The proposed approach successfully was applied to a real case of ISWM in southern Tehran, Iran. The numerical experiments showed the usefulness of the approach to minimize the economic costs of the system under uncertainty. Furthermore, the results verified the strength and effectiveness of the method when experiencing larger deviations between the estimated and actual amounts of the uncertain parameter and in cases of unplanned disruptions in the system network.