| Distribution Inventory Cost Optimization Under Grey and Fuzzy Uncertainty |
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| 引用本文： | LIU Dongbo HUANG Dao CHEN Yujua. Distribution Inventory Cost Optimization Under Grey and Fuzzy Uncertainty[J]. 武汉大学学报:自然科学英文版, 2006, 11(5): 1238-1242. DOI: 10.1007/BF02829243 |
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| 作者姓名： | LIU Dongbo HUANG Dao CHEN Yujua |
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| 作者单位： | [1]Research Institute of Automation, East ChinaUniversity of Science and Technology, Shanghai 200237,China [2]College of Mechanical and Electronic Engineering,Shanghai Normal University, Shanghai 201418, China |
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| 基金项目： | Supported by the Science and Research Foundation of Shanghai Municipal Educational Commssion （05DZ33） |
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| 摘 要： | 0 IntroductionThe bullwhipeffect makes many parameters of supplychainbecome more uncertain[1].The customer demand andre-plenishment lead ti me are i mportant uncertain parameters insupply chaininventory system[2 ,3]. However , many researchesabout inventory control have made strong assumptions takingthe uncertain factors as stochastic[3-6]or deterministic parame-ters[2].These assumptions may make the models less realistic.The stochastic programming and fuzzy programming areusual uncertain pro…
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| 关 键 词： | 灰色模糊变量 系统模拟 神经网络 遗传算法 库存管理 供应链优化 |
| 文章编号： | 1007-1202（2006）05-1238-05 |
| 收稿时间： | 2006-01-10 |
Distribution inventory cost optimization under grey and fuzzy uncertainty |
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| Liu Dongbo,Huang Dao,Chen Yujuan. Distribution inventory cost optimization under grey and fuzzy uncertainty[J]. Wuhan University Journal of Natural Sciences, 2006, 11(5): 1238-1242. DOI: 10.1007/BF02829243 |
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| Authors: | Liu Dongbo Huang Dao Chen Yujuan |
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| Affiliation: | (1) Research Institute of Automation, East China University of Science and Technology, 200237 Shanghai, China;(2) College of Mechanical and Electronic Engineering, Shanghai Normal University, 201418 Shanghai, China |
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| Abstract: | The grey fuzzy variable was defined for the two fold uncertain parameters combining grey and fuzziness factors. On the basis of the credibility and chance measure of grey fuzzy variables, the distribution center inventory uncertain programming model was presented. The grey fuzzy simulation technology can generate input-output data for the uncertain functions. The neural network trained from the inputoutput data can approximate the uncertain functions. The designed hybrid intelligent algorithm by embedding the trained neural network into genetic algorithm can optimize the general grey fuzzy programming problems. Finally, one numerical example is provided to illustrate the effectiveness of the model and the hybrid intelligent algorithm. |
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| Keywords: | grey fuzzy variable grey fuzzy simulation neural network genetic algorithm inventory control supply chain optimization |
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