Solving expert assignment problem using improved genetic algorithm

被引:0
|
作者
Li, Na-Na [1 ,2 ]
Zhang, Jian-Nan [2 ]
Gu, Jun-Hua [2 ]
Liu, Bo-Ying [2 ]
机构
[1] Tianjin Univ, Sch Comp Sci & Technol, Tianjin 300072, Peoples R China
[2] Hebei Ubi Technol, Tianjin 300130, Peoples R China
基金
美国国家科学基金会;
关键词
expert assignment problem; genetic algorithm; ant algorithm; adaptive mutation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Expert assignment is chief and basic work of project review in project management. So it is significant to research how to solve expert assignment problem (EAP). In previous papers, we established the mathematical model of expert assignment problem, and proposed genetic algorithm (GA) and GA using heuristic mutation guide by pheromone (HMP) to solve EAP. Though it has been proven GA and HMP are effective ways for EAP, they have disadvantages of massive redundancy iteration in later period and inferior local search ability. In this paper a modification of GA which introduces adaptive mutation to HMP is proposed to solve EAP. The simulation results show that the new algorithm improves the ability of local search and generates solutions of better quality.
引用
收藏
页码:934 / +
页数:2
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