THE DNA GENETIC ALGORITHM APPLIED FOR SOLVING STOCHASTIC INTEGER PROGRAMMING EXPECTED VALUE MODELS

摘要：

In this paper, how to use DNA genetic algorithm to solve stochastic integer programming expected value models is discussed. Since DNA Genetic algorithm has the merits of plentiful coding, and decoding, conveying complex knowledge flexibly. These merits and the technique of stochastic simulation are combined, which for estimating the random variables of stochastic integer programming expected value models problem. Base on them, a best solution of this problem can be found. The classical newspaper-selling boy problem is calculated for testifying the feasibility and effectiveness of this method.

关键词： Stochastic integer programming Ezpected value models DNA genetic algorithm Stochastic simulation

作者: MING-CHUN WANG WAN-SHENG TANG XIN LIU

作者单位: System Engineering Institute of Tianjin University, Tianjin, 300072, China Tianjin University of Tec System Engineering Institute of Tianjin University, Tianjin, 300072, China Tianjin University of Technology and Education, Tianjin, 300222, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 1020-1024

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）