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

Abstract

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.