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Sustainable closed-loop supply chain for dairy industry with robust and heuristic optimization
•Reduction in run time using the heuristic for large-scale problems.•Using a robust optimization approach and an augmented ε-constraint method.•Higher profit for products with a longer lifetime under the worst-case scenario. This paper supplements the augmented ε-constraint approach with linearizati...
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Published in: | Computers & industrial engineering 2021-07, Vol.157, p.107324, Article 107324 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Reduction in run time using the heuristic for large-scale problems.•Using a robust optimization approach and an augmented ε-constraint method.•Higher profit for products with a longer lifetime under the worst-case scenario.
This paper supplements the augmented ε-constraint approach with linearization using robust optimization and heuristics with an improved algorithm to maximize the total profit and minimize the environmental effects of a sustainable closed-loop supply chain (CLSC) in the dairy industry. The resultant mixed-integer linear programming (MILP) model is applied to a case from the dairy industry and evaluated against several test problems. The pessimistic, optimistic, and worst-case scenarios are considered along with the sensitivity analysis on the profitability of the CLSC concerning the product lifetimes. Our results inform that applying the heuristic on large-scale problems yields a 25% improvement in runtime. Furthermore, products with a longer lifetime under the worst-case scenario yield greater profit than those products with a shorter lifetime under an optimistic scenario. |
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ISSN: | 0360-8352 1879-0550 |
DOI: | 10.1016/j.cie.2021.107324 |