摘要
为了提高动态联盟中企业选择联盟伙伴和优化过程中的效率,提出一种基于Metropolis准则遗传算法的企业动态联盟生成模型.将模拟退火算法中的Metropolis准则与遗传算法相结合,提高企业选择联盟伙伴和优化过程中的效率.1 000次仿真实验表明,标准遗传算法SGA平均需要166次才能找到最优解,而基于Metropolis准则遗传算法(MGA)平均仅需要149次就可以找到最优解.企业选择联盟伙伴和优化时,基于Metropolis准则遗传算法(MGA)可以使企业高效找到最优联盟伙伴.
To enhance the efficiency of corporation partner selection and optimization process in virtual corporations, a genetic algorithm based on Metropolis rule （MGA） and its application in virtual partner selection process is presented. In the model, MGA is used to enhance the efficiency of corporation partner selection and optimization process. After 1 000 times of experiments to gain the optimal result, standard genetic algorithm（SGA） averagely needs 166 runs, while the MGA averagely needs only 149 runs. The experimental results showed that the MGA could gain the optimal result more efficiently than SGA in virtual corporation formation process.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2008年第11期988-992,共5页
Transactions of Beijing Institute of Technology
基金
国家“九七三”计划项目(2007CB310704)
关键词
动态联盟
伙伴选择
基于Metropolis遗传算法
virtual corporation（VC）
partner selection
genetic algorithm based on Metropolis rule（MGA）
