Developing Sustainable Recovery Model Of End-Life Products (Case Study: End-Of Life Vehicle)

Mohebbi, Nazanin; Rad, Abbas; Motameni, Alireza

Developing Sustainable Recovery Model Of End-Life Products (Case Study: End-Of Life Vehicle)

Authors

N. Mohebbi

A. Rad

A. Motameni

Abstract

The purpose of this study is to develope a sustainable recovery model for used vehicle in which economic, environmental and social impacts are balanced. This study is result or purpose based and is applied and in terms of method is mathematical programming modeling – quantitative. In order to collecting required data, a questionnaire of paired comparison applied. As well as data modeling for research in case of research, for solving various problems of mathematical programming model by Hypothetical data documentation and experts ideas in Saipa company gathered. Fuzzy Analytic Hierarchy Process has been set appropriate criteria weight for defining social functions applied. Then, using concepts and principles of mathematical modeling has been paid to determine sets, parameters, variables, objective functions and limitations of the mathematical model for locating car waste recovery sites. Then mathematical modeling provided by multi-objective genetic algorithm solved. In this study proposed hybrid algorithm and simple NSGA-II for solving the model used and compared. Some of test problems randomly generated and solved by both algorithms. Also, case study problem is solved using proposed NSGA-II hybrid algorithm. The analysis of data for this study has been done using Excel and MATLAB. Results show that dismantling facility should be establish in Tehran, Semnan, Khorasan, Tabriz, Kashan, and processing facility should be set in Semnan, Khorasan and Tabriz. Solving the test problems show that the proposed NSGA-II hybrid algorithm in terms of solution quality is better simple NSGA-II algorithm and proposed NSGA-II hybrid algorithm is more time consuming to solve.

Keywords

Reverse Logistics

sustainable development

End-of-Life Products

Multi-Objective Genetic Algorithms

20.1001.1.2322200.1397.22.2.10.1

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