Journal of Quality Engineering and Management

Multi-Objective Green Agile Closed Loop Supply Chain Network Design Using Multi-objective Weed Optimization Algorithm 

Document Type : Original Article

Authors

mehdi dastani 1
sayyed mohammad reza davoodi 2
mehdi karbasian 3
shahram moeeini 4

1 PhD student in Industrial management, Department of management, Islamic Azad University, Isfahan Branch, Isfahan, Iran.

2 Assistant Professor, Department of management, Islamic Azad University, Dehaghan Branch, Dehaghan, Iran.

3 Associate Professor of Industrial Engineering, Malek Ashtar University of Technology.

4 Assistant Professor, Department of Economics, University of Isfahan, Isfahan, Iran.

Abstract
 Success in supply chain implementation depends on how it operates in the face of market changes and customer needs. Agility is a concept recently introduced by supply chain researchers to better design supply chains. Accordingly, and considering the importance of the topic. In this research, the design of Multi-objective closed-loop supply chain network is discussed. Accordingly, and considering the importance of the subject, in this research, the design of Multiobjective closed-loop supply chain network is discussed. The main innovation of this research is the integration of green and agile concepts in supply chain design. To this purpose, a mathematical model with economic, environmental and agility objectives is presented. In order to solve this mathematical model, two methods of Epsilon constraint and Multi-objective weed optimization are proposed. The results of the comparisons between the two methods show that the weed algorithm performs well in terms of different Pareto boundary quality and dispersion indices. At the end, the results are presented for a case study of the Dalan Kuh dairy supply chain and the Pareto border is described. 
 
 

Keywords

Closed loop green supply chain
Epsilon constraint method
Multi-objective Weed optimization Algorithm
Pareto boundary
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Journal of Quality Engineering and Management
Volume 9, Issue 4
Winter 2020
Pages 305-319

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