multi-objective mathematical model for optimizing the collection and recycling of urban waste under conditions of uncertainty(The subject of study : Karaj city)

Subject Areas : Industrial Management

Mohsen Bijanpoor ¹ , Reza Ehtesham Rasi ^{2 *} , Davood Gharakhany ³

1 - Ph.D. Candidate, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 - Assistant Professor, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran,
3 - Assistant Professor, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Received: 2023-05-02 Accepted : 2024-08-21 Published : 2024-12-21

Keywords: two-stage stochastic programming, Lagrange&#039, s release method, linear programming, supply chain, waste management&emsp, ,

Abstract :

In this research, using the double-objective mixed integer linear programming method, an optimal supply chain network for the collection and recycling of urban waste has been presented in terms of separation from the source and uncertainty in the per capita waste production of citizens. Due to the uncertainty in the parameters of the problem, the two-stage stochastic programming method has been used to model the problem. The objective functions include an economic function to minimize investment costs and a social objective function to maximize the amount of recycling. In order to accurately solve the problem on a large scale, the Lagrange release method has been used. To validate and confirm the effectiveness of the model presented in this research, the model was implemented on a case study in the city of Karaj. According to the obtained results, to increase the amount of recycling in the waste supply chain network, more infrastructural and operational investments are needed. By increasing recycling, the harmful environmental and destructive effects of burying and burning waste will be reduced. The Lagrange release solution method can be used as a suitable solution method to reduce the time of solving problems. In this research, it was observed that the Lagrange release method can solve large-scale problems with appropriate accuracy and in less time compared to the commercial cplex solver.

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