Abstract
In this study, we address the production planning problem within a hybrid manufacturing remanufacturing system. This system is composed of a single machine that can work in two modes: the first one that produces new products from raw materials and the second one that produces remanufactured products from returned used products. Our study is based on economic and environmental considerations where the goal is to determine the best manufacturing and remanufacturing plan that satisfies the demand for new and remanufactured products and simultaneously minimizes the total costs included (start-up, production, storage and disposal costs) as well as the minimization of the CO2 emissions generated by the new, remanufactured and disposed of products. A multi-objective mathematical model is established, and an approach based on a non-dominated genetic sorting algorithm (NSGA-II) is introduced; in addition, a technique of order performance by similarity to the ideal solution (TOPSIS) is used to find the best compromise solution among the pareto front obtained by the NSGA-II algorithm. Finally, a computational experiment is implemented to study the influence of carbon emissions from new, remanufactured and discarded items over a production horizon.
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