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

fYear

2010

fDate

17-19 Sept. 2010

Firstpage

706

Lastpage

709

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-6927-7

Type

conf

DOI

10.1109/ICIFE.2010.5609456

Filename

5609456