Fuzzy Two-Stage Supply Chain Problem and Its Intelligent Algorithm

Authors:
Guoli Wang;Yankui Liu;Mingfa Zheng
Affiliations:
College of Mathematics & Computer Science, Hebei University Baoding, Hebei, China 071002;College of Mathematics & Computer Science, Hebei University Baoding, Hebei, China 071002;Department of Applied Mathematics & Physics, Air Force Engineering University Xi'an, Shanxi, China 710051
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

This paper presents a new class of fuzzy two-stage supply chain problems, in which transportation costs and demands are characterized by fuzzy variables with known possibility distributions. Since fuzzy parameters are often with infinite supports, the conventional optimization algorithms cannot be used to solve the proposed supply chain problem directly. To avoid this difficulty, an approximation method is developed to turn the original supply chain problem into a finite dimensional one. Generally, the approximating supply chain problem is neither convex nor linear. So, to solve the approximating supply chain problem, we design a hybrid algorithm by integrating approximation method, neural network (NN) and particle swarm optimization (PSO). Finally, one numerical example is presented to demonstrate the effectiveness of the designed algorithm.