A robust lot sizing problem with ill-known demands
Fuzzy Sets and Systems
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Many companies face material procurement planning (MPP) problem. Since optimizing MPP problem can reduce a large number of total operating costs or reduce the risk of investment, it is important to study the MPP problem. In order to model MPP problem under fuzzy uncertainty, this paper presents a new class of fuzzy two-stage minimum risk MPP model based on credibility theory. This model considers fuzzy variables coefficients related to the market demand and material's spot market price. To solve the two-stage minimum risk MPP model, we design a hybrid algorithm which combines approximation approach (AA), neural network (NN) and particle swarm optimization (PSO). One numerical example is also presented to illustrate the effectiveness of the designed algorithm.