Title :
Fuzzy Minimum-Risk Material Procurement Planning Problem
Author :
Sun, Gao-Ji ; Liu, Yan-Kui
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
Abstract :
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.
Keywords :
approximation theory; fuzzy set theory; neural nets; optimisation; particle swarm optimisation; procurement; approximation approach; credibility theory; fuzzy minimum risk MPP; fuzzy uncertainty; material procurement planning; neural network; particle swarm optimization; Algorithm design and analysis; Approximation algorithms; Costs; Design optimization; Fuzzy sets; Investments; Neural networks; Possibility theory; Procurement; Uncertainty; Credibility Theory; Fuzzy Two-stage model; Material Procurement Planning; Minimum-Risk;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.285