Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation

IMR OpenIR

	Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation
其他题名	Classification-based self-adaptive differential evolution and its application in multi-lateral multi-issue negotiation
	Bi Xiaojun 1; Xiao Jing 1
	2012
发表期刊	FRONTIERS OF COMPUTER SCIENCE
ISSN	2095-2228
卷号	6 期号:4 页码:442-461
摘要	Multi-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.
其他摘要	Multi-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.
关键词	SUPPORT ALGORITHM SCHEME AGENTS SYSTEM differential evolution global optimum e-commerce agent multi-lateral multi-issue negotiation
收录类别	CSCD
语种	英语
资助项目	[National Natural Science Foundation of China]
CSCD记录号	CSCD:4636353
引用统计
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/154244
专题	中国科学院金属研究所
作者单位	1.Harbin Engn University, Sch Informat & Commun Engn, Harbin 150001, Peoples R China 2.中国科学院金属研究所
推荐引用方式 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.