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A Bi-level Meta-heuristic Approach for a Hazardous Waste Management Problem

ماهنامه بین المللی مهندسی، دوره: 33، شماره: 7
Year: 1399
COI: JR_IJE-33-7_017
Language: EnglishView: 219
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Z. Saeidi-Mobarakeh - School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
R. Tavakkoli-Moghaddam - School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
M. Navabakhsh - School of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
H. Amoozad-Khalili - Department of Industrial Engineering, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran


This study concentrates on designing a medical waste management system with a hierarchical structure, including a local government and a waste management planner. The upper-level seeks to design and control the waste management facilities by minimizing the environmental risks related to the disposal of medical waste. While, the lower-level model is to determine the waste collection plans by only minimizing its total operational costs. Therefore, this study develops a bi-level mathematical model, in which the benefits of the both stakeholders are taken into account. As this problem poses difficulty in searching for the optimal solution, a bi-level meta-heuristic approach based on the Genetic Algorithm (GA) is employed for solving the problem. Finally, a case study is conducted to show that the proposed model and solution approach are practical and efficient.


Hazardous Waste Management Location , routing Problem Bi , level Programming Meta , Heuristic Algorithm

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This Paper COI Code is JR_IJE-33-7_017. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

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Saeidi-Mobarakeh, Z. and Tavakkoli-Moghaddam, R. and Navabakhsh, M. and Amoozad-Khalili, H.,1399,A Bi-level Meta-heuristic Approach for a Hazardous Waste Management Problem,

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Type of center: Azad University
Paper count: 11,783
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