| Abstract: | Reverse logistics aims at capturing the remaining value in end-of-use products. This also means saving natural resources, energy, clean air and water, landfill space, and money. Strategic planning (also called designing) of a reverse supply chain is a challenging problem due to various crucial issues, such as what end-of-use products to collect, where to collect them, how to reprocess them, where to reprocess them, etc. To this end, this paper addresses the following two crucial issues, and proposes a quantitative decision-making model for each of them: (i) how to select efficient collection centres? and (ii) how to evaluate whether repairing an end-of-use product is more sensible than remanufacturing/recycling the same? For the first problem, we propose a Linear Physical Programming model, and for the second problem, we employ Fuzzy Logic and Bayesian Updating. The models are demonstrated via numerical examples. |
