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Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation
Alternative TitleClassification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation
Bi Xiaojun1; Xiao Jing1
2012
Source PublicationFRONTIERS OF COMPUTER SCIENCE
ISSN2095-2228
Volume6Issue:4Pages:442-461
AbstractMulti-lateral multi-issue negotiations are the most complex realistic negotiation problems. Automated approaches have proven particularly promising for complex negotiations and previous research indicates evolutionary computation could be useful for such complex systems. To improve the efficiency of realistic multi-lateral multi-issue negotiations and avoid the requirement of complete information about negotiators, a novel negotiation model based on an improved evolutionary algorithm p-ADE is proposed. The new model includes a new multi-agent negotiation protocol and strategy which utilize p-ADE to improve the negotiation efficiency by generating more acceptable solutions with stronger suitability for all the participants. Where p-ADE is improved based on the well-known differential evolution (DE), in which a new classification-based mutation strategy DE/rand-to-best/pbest as well as a dynamic self-adaptive parameter setting strategy are proposed. Experimental results confirm the superiority of p-ADE over several state-of-the-art evolutionary optimizers. In addition, the p-ADE based multiagent negotiation model shows good performance in solving realistic multi-lateral multi-issue negotiations.
Other AbstractMulti-lateral multi-issue negotiations are the most complex realistic negotiation problems. Automated approaches have proven particularly promising for complex negotiations and previous research indicates evolutionary computation could be useful for such complex systems. To improve the efficiency of realistic multi-lateral multi-issue negotiations and avoid the requirement of complete information about negotiators, a novel negotiation model based on an improved evolutionary algorithm p-ADE is proposed. The new model includes a new multi-agent negotiation protocol and strategy which utilize p-ADE to improve the negotiation efficiency by generating more acceptable solutions with stronger suitability for all the participants. Where p-ADE is improved based on the well-known differential evolution (DE), in which a new classification-based mutation strategy DE/rand-to-best/pbest as well as a dynamic self-adaptive parameter setting strategy are proposed. Experimental results confirm the superiority of p-ADE over several state-of-the-art evolutionary optimizers. In addition, the p-ADE based multiagent negotiation model shows good performance in solving realistic multi-lateral multi-issue negotiations.
KeywordSUPPORT ALGORITHM SCHEME AGENTS SYSTEM differential evolution global optimum e-commerce agent multi-lateral multi-issue negotiation
Indexed ByCSCD
Language英语
Funding Project[National Natural Science Foundation of China]
CSCD IDCSCD:4636353
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/154244
Collection中国科学院金属研究所
Affiliation1.Harbin Engn University, Sch Informat & Commun Engn, Harbin 150001, Peoples R China
2.中国科学院金属研究所
Recommended Citation
GB/T 7714
Bi Xiaojun,Xiao Jing. Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation[J]. FRONTIERS OF COMPUTER SCIENCE,2012,6(4):442-461.
APA Bi Xiaojun,&Xiao Jing.(2012).Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation.FRONTIERS OF COMPUTER SCIENCE,6(4),442-461.
MLA Bi Xiaojun,et al."Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation".FRONTIERS OF COMPUTER SCIENCE 6.4(2012):442-461.
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