A Hybrid Intelligent Algorithm for Fuzzy Dynamic Inventory Problem
Year: 2006
Journal of Information and Computing Science, Vol. 1 (2006), Iss. 4 : pp. 235–244
Abstract
In this paper, a fuzzy inventory problem with multiple commodities is casted into a dynamic pro- gramming model with continuous state space and decision space. In order to solve the dynamic programming model, genetic algorithms are used to get samples of the optimal cost functions, and then neural networks are trained to approximate the optimal cost function on a randomly generated sample set, which may bypass “the curse of dimensionality”. A hybrid intelligent algorithm is thus produced to get the optimal cost functions functions that represented by neural networks. Lastly, a numerical example is given for illustrating purpose
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22834
Journal of Information and Computing Science, Vol. 1 (2006), Iss. 4 : pp. 235–244
Published online: 2006-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10