Abstract
Designing an effective collection process is strategically important due to its impact on product-recovery, profit and responsiveness of overall closed-loop supply chain (CLSC). In this paper, we propose a product-recovery framework which models consumers’ willingness to accept a product exchange offer (PEO) as non-linear function of discount amount offered to them on returning used product and utility they obtain on receiving the new product. The proposed recovery framework is then integrated with a multi-objective optimization model, which takes into account the responsiveness of both forward and reverse supply chain, in order to maximize profit and responsiveness of the overall CLSC. The optimization model is solved using a modified interactive fuzzy goal programming technique, which allows the decision makers to adjust lower and/or upper bound of the objective functions during the interactive decision making process. The developed optimization model determines optimal value of discount, optimal return and remanufacturing quantity of used products, and optimal manufacturing quantity of fresh-new products. The analysis suggests a trade-off between amount of discount offered to consumers on returning used products and perceived quality of the new product while accepting the PEO.
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