Outsourcing Evaluation in RL Network
Abstract
This thesis addresses the qualitative investigation of the reverse logistics and outsourcing and a quantitative analysis of reverse logistic networks that covenant with the option of outsourcing or in-house remanufacturing. Two models are proposed with an objective of contributing to decision making process for reverse logistics outsourcing. The purpose is to find a set of decisions throughout the product life cycle that maximizes both outsourcing and in-house remanufacturing. These models will also verify two hypotheses: outsourcing is more likely to be an optimal solution when variance in return rate is high, and also when the product life cycle is short in length. Then, a solution approach is designed for solving this problem which follows MDP that considers the firm following a dynamic capacity model and also a stationary capacity model. Finally, computational analyses are performed to demonstrate the applicability of the model. Numerical results justify the two hypotheses.
