Abstract
Due to the competitive environment, supply chain management is an important subject in the world of economy. It affects all of the activities including products manufacturing, flow between facilities and costs. In this research, a mixed-integer linear programming model is considered which included supplier, plants, demand markets, collection centres, and disposal centre. The closed-loop supply chain model is bi-objective. So, it is solved by the e-constraint method and non-dominated sorting genetic algorithm-II. In order to improve the meta-heuristic algorithm's efficiency, its parameters are tuned by Taguchi method. Afterward, the different dimensions of the model are considered and the problem is rewritten as a single-objective model and solved by LINGO software and the genetic algorithm using MATLAB software to compare the efficiency of the LINGO and meta-heuristic algorithm. In small-scale problems, solving by LINGO software and in large-scale problems, solving by meta-heuristic algorithms are more efficient.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Applied Decision Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
