文章基本信息

标题：Stochastic Programming Models and Hybrid Intelligent Algorithm for Unbalanced Bidding Problem
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作者：Xingzi Liu ; Liang Lin ; Dongran Zang 等
期刊名称：Computer and Information Science
印刷版ISSN：1913-8989
电子版ISSN：1913-8997
出版年度：2009
卷号：2
期号：1
页码：188
DOI：10.5539/cis.v2n1P188
出版社：Canadian Center of Science and Education
摘要：The expected value model and the chance-constrained programming model for unbalanced bidding problem are established on the condition that quantities of each activity are stochastic variables and the total project is finished smoothly in this paper. These models can make the unbalanced bidding price more reasonable and applicable. In order to solve these models, stochastic simulation, neural network and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, a numerical example is given to illustrate its effectiveness.