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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Main Authors: Teerapat Threepatcharatip, Samerkae Somhom
Format: Book Series
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901479938&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45259
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-452592018-01-24T06:07:29Z A guided genetic algorithm for bilateral negotiation with incomplete information Teerapat Threepatcharatip Samerkae Somhom 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. 2018-01-24T06:07:29Z 2018-01-24T06:07:29Z 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/6653943832/45259
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description 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.
format Book Series
author Teerapat Threepatcharatip
Samerkae Somhom
spellingShingle Teerapat Threepatcharatip
Samerkae Somhom
A guided genetic algorithm for bilateral negotiation with incomplete information
author_facet Teerapat Threepatcharatip
Samerkae Somhom
author_sort 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
title_full_unstemmed A guided genetic algorithm for bilateral negotiation with incomplete information
title_sort guided genetic algorithm for bilateral negotiation with incomplete information
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901479938&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45259
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