Abstract
Municipal solid waste management (MSW) is a factor that affects environmental pollution and the spread of diseases in cities. Therefore, an efficient MSW management system results in reducing the cost of environmental impact by tackling the processes of waste collection, recycling, and disposal. In this study, a biobjective optimization model is developed which aims to minimize the costs of facility location and transportation planning and the emission of environmental pollutants. Furthermore, to consider the uncertain nature of the problem, demand or the volume of the generated waste is considered as a random parameter. As a result, a stochastic mathematical programming model with probable constraints is developed. To solve and validate the model, the ε-constraint approach has been employed. Moreover, for a real-world application of the proposed model, a case study is implemented in Qazvin, Iran. Finally, various problems are solved for different levels of reliability and an efficient MSW system is designed for each of them. Results show that the proposed method was able to achieve Pareto solutions where managers can decide to choose one of them based on their priorities in comparison with the current status. Moreover, results revealed cost and emission would be reduced by increasing confidence level. Finally, a comparison is made between our proposed ε-constraint method and one of the recently used solution approaches.
Highlights
Municipal solid waste (MSW) is the generated solid waste in urban residential areas
The case study is solved based on the proposed model
If waste is not collected in time, it will cause pollution. erefore, the issue of waste collection planning is of great importance. is research has tried to provide a comprehensive model for the problem of location and use of facilities for waste collection with the aim of minimizing the total costs and pollution caused by the transportation system
Summary
Municipal solid waste (MSW) is the generated solid waste in urban residential areas. MSW includes the generated waste by residential houses, commercial units, industrial sectors, and institutional units such as schools, hospitals, care centers, and public centers such as streets, markets, bus stops, and parks [1, 2]. Is study aims to develop an efficient planning system for the collection and transportation of municipal waste [4, 5]. For this purpose, vehicle routing is one of the main components of the proposed mathematical model while considering the uncertain nature of the demand in the problem. Routing the waste collection vehicles and their allocation and considering the various types of waste are the main challenges that municipalities usually face in planning for municipal waste collection Using these concepts and analyzing the results, various policies can be evaluated and the optimal policy can be selected [6, 7].
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