A guided genetic algorithm for bilateral negotiation with incomplete information
Reaching 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 alg...
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th-cmuir.6653943832-535262018-09-04T09:50:50Z A guided genetic algorithm for bilateral negotiation with incomplete information Teerapat Threepatcharatip Samerkae Somhom Engineering Reaching 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. 2018-09-04T09:50:50Z 2018-09-04T09:50:50Z 2014-01-01 Book Series 10226680 2-s2.0-84901479938 10.4028/www.scientific.net/AMR.931-932.1422 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901479938&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53526 |
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Engineering Teerapat Threepatcharatip Samerkae Somhom A guided genetic algorithm for bilateral negotiation with incomplete information |
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Reaching 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. |
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Book Series |
author |
Teerapat Threepatcharatip Samerkae Somhom |
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Teerapat Threepatcharatip Samerkae Somhom |
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Teerapat Threepatcharatip |
title |
A guided genetic algorithm for bilateral negotiation with incomplete information |
title_short |
A guided genetic algorithm for bilateral negotiation with incomplete information |
title_full |
A guided genetic algorithm for bilateral negotiation with incomplete information |
title_fullStr |
A guided genetic algorithm for bilateral negotiation with incomplete information |
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A guided genetic algorithm for bilateral negotiation with incomplete information |
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guided genetic algorithm for bilateral negotiation with incomplete information |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901479938&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53526 |
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