Mathematical Model for Optimizing Green Waste Recycling Networks Considering Outsourcing

Abstract

The rapid growth of industry and economy and the increase in incomes have led to the influx of people to big cities and thus a sharp increase in waste production. Inappropriate waste management damages city infrastructure and affects community health and environment. Governments need to plan and implement integrated management from waste production to final disposal for achieving sustainable solution. This paper presents a bilevel multiobjective programming model for the design and planning of a municipal solid waste management (MSWM) network. The MSWM network includes production sites, transfer stations (TSs), treatment centers (TCs), waste recycling centers, and landfill sites. The municipality outsources waste through auctions. The Stackelberg game method is used in the context of a bilevel problem for the design of an MSWM network in auction conditions. The municipality, as the primary decision maker (DM), decides on the locations of TCs, TSs, and landfills, the technology type and capacity of TSs and treatment facilities, as well as on waste outsourcing and selection of the winning company. The bidders as followers set their bids in a way that maximizes their profit and winning chance at the auction. The proposed model is transformed into a single-level multiobjective mixed-integer linear programming (MOMILP) model using the Karush−Kuhn−Tucker conditions. Then, the augmented ε-constrained method is used to solve the multiobjective model. A real case study in the Qazvin province of Iran is conducted to show the applicability of the proposed approach. The results show that the presented MOMILP model is useful in designing an integrated MSWM network trading off between total costs and total greenhouse gas emission based on the main DM priorities.

How to Measure Sustainability in the Supply Chain Design: An Integrated Proposal from an Extensive and Systematic Literature Review

“…Research articles focused on waste aim to diminish the environmental impact by preventing waste generation, ultimately decreasing greenhouse gas emissions [149,199,389,406,439,479]. Thus, these articles examine the effect of waste supply chain management decisions on the environment in search of greater efficiency [112].…”

Source separation, transportation, pretreatment, and valorization of municipal solid waste: a critical review

“…Subsequently, fossil energy depletion, environmental pollution, human health, economic costs, and the aesthetics of C&T facilities, in turn, caused public social concern, that is, citizens' subjective choices (Chester et al, 2008 ). Therefore, the objectives of optimizing C&T techniques are mostly around one or several factors of economic cost, environmental and social impact, which are also the goal of sustainable development (Bulatov et al, 2021 ; Yousefloo & Babazadeh, 2020 ).…”

“…Tracking hotspots and future directions of C&T techniques through literature analysis, the following four points are summarized in this review. (i) The shift from single-objective to multi-objective analysis: from the beginning only to focus on the shortest route (Fiorucci et al, 2003 ), to the pursuit of the optimal vehicle routes and environmental effects (Ferronato et al, 2020 ; Hannan et al, 2020 ; Yousefloo & Babazadeh, 2020 ), and then more studies involved social effects (Chabok et al, 2020 ; Yadav et al, 2020 ). Bányai et al put forward a cyber-physical system that included routing, distribution, and scheduling issues to simulate the urban waste C&T process, while minimizing overall operating costs and the environmental effects of CO 2 emissions simultaneously (Bányai et al, 2019 ).…”

“…However, it is more targeted at MSW that generates economic benefits for waste collectors. Cooperation with municipalities, such as outsourcing, can transition from informal to formal recycling (Yousefloo & Babazadeh, 2020 ). Furthermore, with the closure of some markets for recycled goods in China, the fate of recycled products in some developed countries is also forced to be rethought (Wang et al, 2019b ).…”

Multiobjective Mathematical Optimization Model for Municipal Solid Waste Management with Economic Analysis of Reuse/Recycling Recovered Waste Materials

“…(Rudy, 2004;Michael, 2007). According to Yousefloo and Babazadeh (2020), the high rate of people influx into capital cities gave birth to the increase of waste production and hence the need for policymakers to manage such wastes for proper town planning of the scarce resources. They proposed a bilevel multiobjective mixed-integer linear programming (MILP) model for designing and planning of MSW network considering outsourcing via auctions.…”