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

作　　者：Xiaojun BI Jing XIAO 

机构地区：[1]School of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China [2]School of Information Engineering,Liaoning Provincial College of Communications,Shenyang 110122,China

出　　处：《Frontiers of Computer Science》2012年第4期442-461,共20页中国计算机科学前沿（英文版）

摘　　要：Multi-lateral multi-issue negotiations are the most complex realistic negotiation problems. Automated ap- proaches have proven particularly promising for complex ne- gotiations and previous research indicates evolutionary com- putation could be useful for such complex systems. To im- prove the efficiency of realistic multi-lateral multi-issue ne- gotiations and avoid the requirement of complete informa- tion about negotiators, a novel negotiation model based on art 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 negotia- tion 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 pa- rameter 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 multi- agent negotiation model shows good performance in solving realistic multi-lateral multi-issue negotiations.Multi-lateral multi-issue negotiations are the most complex realistic negotiation problems. Automated ap- proaches have proven particularly promising for complex ne- gotiations and previous research indicates evolutionary com- putation could be useful for such complex systems. To im- prove the efficiency of realistic multi-lateral multi-issue ne- gotiations and avoid the requirement of complete informa- tion about negotiators, a novel negotiation model based on art 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 negotia- tion 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 pa- rameter 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 multi- agent negotiation model shows good performance in solving realistic multi-lateral multi-issue negotiations.

关 键 词：differential evolution global optimum E-COMMERCE AGENT multi-lateral multi-issue negotiation 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TN911.72[自动化与计算机技术—计算机科学与技术]