一种电子商务中基于混合遗传算法的多边多议题协商
Multi-Lateral Multi-Issue Negotiation Based on Hybrid Genetic Algorithm and Its Application in E-Commerce
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摘要: 为了提高基于智能体电子商务多边多议题合作协商中的协商效率,提出将混合遗传算法(HGA)应用于该协商中. 对4种遗传算法分别进行1000次的实验对比,结果表明,要达到同样协商最优解,标准遗传算法(SGA)平均需要185次协商,基于Metropolis准则遗传算法(MGA)平均需要176次,自适应遗传算法(AGA)平均需要169次,而混合遗传算法(HGA)平均仅需要153次. 求解多边多议题合作协商问题中,HGA可以使得协商当中的agent高效达到最优解.Abstract: To enable agents negotiate more efficiently in multi-lateral multi-issue cooperative negotiations in multi-agent based e-commerce, a hybrid genetic algorithm (HGA) is presented. After 1000 times of experiments for four kinds of agents to gain satisfying result, standard genetic algorithm(SGA) averagely needs negotiation of 185 runs, genetic algorithm based on Metropolis rule(MGA) averagely needs 176 runs, adaptive genetic algorithm(AGA) averagely needs 169 runs, while the HGA averagely needs only 153 runs. Experimental results showed that the HGA can gain optimal negotiation result more efficiently than the other three kinds of genetic algorithms in multi-lateral multi-issue cooperation negotiation.
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