Green- Closed Loop Supply Chain Network Design by Considering Customer Relationship Management and solving it using Multi-Objective Genetic Algorithm
Subject Areas : Sustainable DevelopmentMohsen Etemad 1 , Navid Nezafati 2 * , Mohammad Reza Fathi 3
1 - Ph.D. Student of Industrial Management, Islamic Azad University Central Tehran Branch, Tehran, Iran
2 - Assistant Professor., Department of Management and Accounting, Shahid Beheshti University, Tehran, Iran. *(Correspondence Author)
3 - Associate Professor., Department of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran.
Keywords: Supply Chain Network Design, Green Supply Chain, Customer Relationship Management, Multi-objective Genetic Algorithm.,
Abstract :
Background and Objective: Increasing greenhouse gas emissions and pollutants has led organizers and researchers to seek to design and set up networks that focus on environmental factors and reduce pollutants in all sectors. Therefore, the main objective of this paper is to present a fuzzy mathematical programming model for the green closed loop supply chain network, taking into account customer relationship management.Method: This is an applied-development study implemented in Saba Battery Company. In this study, a mixed integer linear programming model is proposed for designing a closed loop supply chain network that seeks to minimize costs and minimize environmental impacts. Also, the concept of customer relationship management in the form of the third objective function has been added to maximize the amount of worn-out product collected to this model.Findings: Given that the proposed model belongs to the NP-hard category, a multi-objective genetic algorithm is used to solve the model, and finally, the Pareto's solutions are determined. Based on the results, the two objectives of the economic and environmental objectives are contradictory. That is, moving each one toward the desired one requires movement of the other objective function to the undesirable.Discussion and Conclusion: In this research, the proposed mathematical programming model has been solved with a multi-objective genetic algorithm, which results indicate the location and capacity of the facility, the amount of production, the amount of inventory and the amount of transportation of the products.
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