Investigate an imperfect green production system considering rework policy via Teaching-Learning-Based Optimizer algorithm

•Imperfect green production system with rework policy.•Optimal control theory.•Teaching-Learning-Based Optimizer Algorithm.•Statistical significant test. Green products have achieved a wide reputation in the current competitive market in the last few decades. Again, the imperfect production rate dur...

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Bibliographic Details
Published in:Expert systems with applications Vol. 214; p. 119143
Main Authors: Ali, Hachen, Das, Subhajit, Akbar Shaikh, Ali
Format: Journal Article
Language:English
Published: Elsevier Ltd 15.03.2023
Subjects:
Green production
Imperfect production
Optimal control
Rework policy
Salvage
Teaching-Learning-Based Optimizer algorithm (TLBO)
Imperfect production
Green production
Salvage
Teaching-Learning-Based Optimizer algorithm (TLBO)
Optimal control
Rework policy
ISSN:0957-4174
Online Access:Get full text
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Summary:•Imperfect green production system with rework policy.•Optimal control theory.•Teaching-Learning-Based Optimizer Algorithm.•Statistical significant test. Green products have achieved a wide reputation in the current competitive market in the last few decades. Again, the imperfect production rate during production imposes a minor issue in generating optimal revenue for a manufacturing firm. Primarily focusing on these two factors, the current study demonstrates an imperfect production inventory system of green products by considering two activities regarding business accommodation of imperfectly manufactured products: (i) rework and (ii) salvage. The primary purpose of this work is to study the optimal policy of a manufacturing firm based on production control, the greenness of the products, and the rework or salvage of defective products. Here, consumers’ demand is green level and selling price dependent. Further, production costs are green-level and production rate dependent. The average profits of the system (corresponding to both cases) appear to be highly non-linear. They necessitate the employment of a meta-heuristic algorithm (viz., the Teaching-Learning-Based Optimizer Algorithm). From the numerical example, it is observed that the reworked policy appears to be more profitable than the salvage policy for the firm. Finally, a sensitivity analysis is carried out to draw some fruitful conclusions.
ISSN:0957-4174
DOI:10.1016/j.eswa.2022.119143