Title :
Research on multi-lateral multi-issue negotiation based on hybrid genetic algorithm in e-commerce
Author :
Song, Qiang ; Zhang, Han
Author_Institution :
Comput. Dept., Anyang Inst. of Technol., Anyang, China
Abstract :
To enable agents negotiate more efficiently in multilateral multi-issue cooperative negotiations in multi-agent based on e-commerce, a hybrid genetic algorithm (HGA) is presented and applied in the negotiation. After compare of 1000 times of experiments for four kinds of genetic algorithm, the result shows that standard genetic algorithm (SGA) averagely needs negotiation 185 times, genetic algorithm based on Metropolis rule (MGA) averagely needs 176 times, adaptive genetic algorithm (AGA) averagely needs 169 times, while the HGA averagely needs only 153 times. The HGA can gain optimal negotiation result more efficiently than the other three kinds of genetic algorithms in multi-lateral multi-issue cooperation negotiation.
Keywords :
electronic commerce; genetic algorithms; HGA; adaptive genetic algorithm; e-commerce; hybrid genetic algorithm; metropolis rule average; multi-lateral multi-issue cooperation negotiation; Algorithm design and analysis; Binary codes; Biological cells; Companies; Convergence; Encoding; Process control; E-commerce; agent; hybrid genetic algorithm; multi-literal multi-issue negotiation;
Conference_Titel :
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-6927-7
DOI :
10.1109/ICIFE.2010.5609456
