Abstract
In this paper, the optimal pricing decisions in a remanufacturing system with random fuzzy quality level of used products and random demand are considered. Expected profit maximization model, (a;b)-profit maximization model and chance maximization model are proposed according to different management goals. Then hybrid intelligent algorithm integrating random fuzzy simulation, neural network and genetic algorithm is developed for solving proposed models. Finally, numerical examples are explored to analyze the effects of the sensitivity of demand to price on the system, and to show the feasibility and efficiency of proposed models.
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