A Green Hazardous Waste Location-routing Problem Considering the Risks Associated with Transportation and Population

被引:10
|
作者
Delfani, F. [1 ]
Kazemi, A. [1 ]
Seyedhosseini, S. M. [2 ]
Niaki, S. T. A. [3 ]
机构
[1] Islamic Azad Univ, Fac Ind & Mech Engn, Qazvin Branch, Qazvin, Iran
[2] Iran Univ Sci & Technol, Sch Ind Engn, Tehran, Iran
[3] Sharif Univ Technol, Dept Ind Engn, Tehran, Iran
来源
INTERNATIONAL JOURNAL OF ENGINEERING | 2020年 / 33卷 / 11期
关键词
Hazardous Waste; Location-routing Problem; Green Emissions; Stochastic Constraint; Multi-objective Optimization; MUNICIPAL SOLID-WASTE; SUPPLY CHAIN; MODEL; LOGISTICS; ALLOCATION; OPTIMIZATION; ALGORITHMS; MANAGEMENT; SELECTION; NETWORK;
D O I
10.5829/ije.2020.33.11b.18
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The researches on environmental and sustainability are an active topic, especially in the waste management. As such, the hazardous waste optimization is an active research topic in developing countries which may be integrated with carbon emissions and green subjects. This grand challenge motivates the current research to contribute a new multi-objective optimization model to address the green hazardous waste location-routing problem. The proposed multi-objective optimization model establishes four objectives simultaneously for the first time. In addition to the total cost and the greenhouse gas emissions of the transportation systems as the two main objectives, another objective function aims to minimize the risk of transportation of the hazardous waste alongside the waste residue associated with the people's exposure around transportation paths. Furthermore, the total risk linked with the population in a certain radius around the treatment and disposal centers is minimized As the proposed model is complex with conflicting objectives, several multi-objective decision making (MODM) tools are employed and compared with each other based on different test problems associated with an industrial example. Based on the solution quality and the computational time, the technique for the order of preference by similarity to the ideal solution (TOPSIS) is selected as the strongest technique to assess the performances of all five MODM methodologies.
引用
收藏
页码:2272 / 2284
页数:13
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