An Integrated Optimization Model of a Closed-Loop Supply Chain Under Uncertainty
This paper studies a closed-loop supply chain, mainly consisting of positive selling, repairing, and remanufacturing under uncertainty. Then, we build a model for the closed-loop supply chain integration and optimization under uncertainty, in which a comprehensive utility function is used to clarify the random parameters, so that we can transform the model into a mixed integer programming model and do further analysis by hybrid genetic algorithm. The feasibility and validity of the model are verified by illustrative examples. This paper provides an effective decision-making tool for the closed-loop supply chain design. It is useful for the integration of forward and reverse supply chains.
KeywordsClosed-loop supply chain Products repair Modular reutilization Uncertainty environment Hybrid genetic algorithm
This paper is supported by the project from National Key Technologies R & D Program of China (2012BAH20B03) and Supported by Foundation of Hebei University of Science and Technology (XL200761).
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