A multi-objective optimization of closed-loop supply chain problem with vehicle routing
1 Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram (IIITDM), Chennai, India.
2 Department of Mechanical Engineering, Sri Krishna College of Technology, Coimbatore, India
Research Article
Global Journal of Engineering and Technology Advances, 2021, 06(02), 121-130.
Article DOI: 10.30574/gjeta.2021.6.2.0009
Publication history:
Received on 05 January 2021; revised on 30 January 2021; accepted on 02 February 2021
Abstract:
Product recovery has become significant business strategies to increase a competitive edge in business and also in the society. Parts from discarded products due to rapid advancement and post-consumer products before & after end-of-life (EOL) are recovered to reduce landfill waste and to have become a part of circular economy. Product recovery is made possible with the help of Closed-loop supply chain (CLSC). This paper concentrates on multi-period, multi-product, and multi-echelon Closed Loop Green Supply Chain (CLGSC) network. A bi-objective (cost and emission) Mixed Integer Linear Programming (MILP) model has been formulated for the network and has been optimized using Goal Programming approach and Genetic Algorithm. Results are discussed for providing some managerial insights of the model.
Keywords:
Closed Loop Supply Chain; Product Recovery; Goal Programming; Emission; Vehicle Routing; Green Supply Chain
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0