As market demand for remanufactured products increases and environmental legislation puts further enforcement on Original Equipment Manufacturers (OEMs), remanufacturing is becoming an important business. However profitability of salvaging operations is still a challenge in remanufacturing industry. Several factors influence the cost effectiveness of remanufacturing operations, including uncertainties in the quantity of return flows and market demand as well as variability in the quality of received items. In this study, we have developed a stochastic optimization model based on chance constrained programing to deal with these sources of uncertainties in take-back and inventory planning systems. The main purpose of the model is to determine the best upgrade level for a received product with certain quality level with the aim of maximizing profit.
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