DocumentCode
3314085
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
Volume
7
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
629
Lastpage
633
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.285
Filename
4668052
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