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Volume 1, Issue 4
A Hybrid Intelligent Algorithm for Fuzzy Dynamic Inventory Problem

J. Info. Comput. Sci. , 1 (2006), pp. 235-244.

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  • 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
  • Keywords

Fuzzy variable, inventory, dynamic programming, neural network, genetic algorithm

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COPYRIGHT: © Global Science Press

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@Article{JICS-1-235, author = {}, title = {A Hybrid Intelligent Algorithm for Fuzzy Dynamic Inventory Problem}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {1}, number = {4}, pages = {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 }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22834.html} }
TY - JOUR T1 - A Hybrid Intelligent Algorithm for Fuzzy Dynamic Inventory Problem AU - JO - Journal of Information and Computing Science VL - 4 SP - 235 EP - 244 PY - 2024 DA - 2024/01 SN - 1 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22834.html KW - Fuzzy variable, inventory, dynamic programming, neural network, genetic algorithm AB - 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
. (2024). A Hybrid Intelligent Algorithm for Fuzzy Dynamic Inventory Problem. Journal of Information and Computing Science. 1 (4). 235-244. doi:
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