RESEARCH ON THE SOLUTION MODELS AND METHODS FOR RANDOM ASSIGNMENT PROBLEMS BASED ON SYNTHESIS EFFECT AND GENETIC ALGORITHM

摘要：

In this paper, we systematically discuss the assignment problem whose efficiency are random variables. Firstly, by using the restriction and complementary relation between mathematical expectation and variance in decision making and the synthesis effect description of random variable, we propose a solution model for random assignment problem. Further, by combining the characteristic of assignment problem, we give the concrete scheme based on genetic algorithm. Finally, we consider its convergence by using Markov chain theory, and analyze its performance through an example. All these indicate that, this solution model can effectively merge decision preferences into the assignment process, it possess many features of strong interpretability, easy operation and higher computation efficiency, so it can be widely used in many fields such as manufacturing and management, optimization scheduling etc.

关键词： Random assignment problem variance synthesis effect mathematical ezpectation genetic algorithm Markov chain

作者: ZHI-CHEN TONG CHEN-XIA JIN

作者单位: School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, 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: 1008-1013

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）