Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/53526
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dc.contributor.authorTeerapat Threepatcharatipen_US
dc.contributor.authorSamerkae Somhomen_US
dc.date.accessioned2018-09-04T09:50:50Z-
dc.date.available2018-09-04T09:50:50Z-
dc.date.issued2014-01-01en_US
dc.identifier.issn10226680en_US
dc.identifier.other2-s2.0-84901479938en_US
dc.identifier.other10.4028/www.scientific.net/AMR.931-932.1422en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901479938&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/53526-
dc.description.abstractReaching an agreement between negotiators is a complex process. The complexity of the problem is depicted by the difference preference of negotiators, the size of the solution space and the negotiation procedure. The aim of this study is to develop an automated negotiation method using a genetic algorithm as a mechanism. The proposed method uses theestimation of the zone of agreementtoguide negotiation. Time and joint utility are used as performance indicators. The result shows that the proposed method hasa better time usage than others'.However, our method could have poor value of joint utility in some cases. A likely explanation is that the progress rate of the negotiators affects the joint payoff. © (2014) Trans Tech Publications, Switzerland.en_US
dc.subjectEngineeringen_US
dc.titleA guided genetic algorithm for bilateral negotiation with incomplete informationen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvanced Materials Researchen_US
article.volume931-932en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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