A Stackelberg single-period supply chain inventory model with weighted possibilistic mean values under fuzzy environment

This paper considers a single-period product inventory control in a distributed supply chain, which is composed of one manufacturer and one retailer and operates in the environment of uncertain market demand. A Stackelberg model with fuzzy demand is first developed, with using a L-R fuzzy number with a general membership function to depict the fuzzy market demand, and through adopting the weighted possibilistic mean value method to rank the retailer and the manufacturer's fuzzy profits, the risk preference of decision maker is also taken into consideration in the model. A special case where the market demand is assumed to be a triangular fuzzy number is further considered, and Genetic Algorithm and Pattern Search Algorithm are adopted to obtain the optimal solutions of the Stackelberg model. At last, numerical examples are used to illustrate the proposed model and sensitivity analyses are provided to get managerial implications.

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