A bi-objective multi-period closed-loop supply chain network under uncertain demand. (17th June 2020)
- Record Type:
- Journal Article
- Title:
- A bi-objective multi-period closed-loop supply chain network under uncertain demand. (17th June 2020)
- Main Title:
- A bi-objective multi-period closed-loop supply chain network under uncertain demand
- Authors:
- Olfati, Marjan
Javadian, Nikbakhsh - 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.
- Is Part Of:
- International journal of applied decision sciences. Volume 13:Number 3(2020)
- Journal:
- International journal of applied decision sciences
- Issue:
- Volume 13:Number 3(2020)
- Issue Display:
- Volume 13, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 13
- Issue:
- 3
- Issue Sort Value:
- 2020-0013-0003-0000
- Page Start:
- 363
- Page End:
- 385
- Publication Date:
- 2020-06-17
- Subjects:
- closed-loop supply chain -- CLSC mixed-integer linear programming -- MILP -- e-constraint -- non-dominated sorting genetic algorithm-II -- NSGA-II -- Taguchi method
Decision making -- Periodicals
Management science -- Periodicals
658.403005 - Journal URLs:
- http://inderscience.metapress.com/content/121094 ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 1755-8077
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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British Library STI - ELD Digital store - Ingest File:
- 23492.xml