A two-stage win–win multiattribute negotiation model: optimization and then concession

Li Pan, Xudong Luo*, Xiangxu Meng, Chunyan Miao, Minghua He, Xingchen Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Many automated negotiation models have been developed to solve the conflict in many distributed computational systems. However, the problem of finding win-win outcome in multiattribute negotiation has not been tackled well. To address this issue, based on an evolutionary method of multiobjective optimization, this paper presents a negotiation model that can find win-win solutions of multiple attributes, but needs not to reveal negotiating agents' private utility functions to their opponents or a third-party mediator. Moreover, we also equip our agents with a general type of utility functions of interdependent multiattributes, which captures human intuitions well. In addition, we also develop a novel time-dependent concession strategy model, which can help both sides find a final agreement among a set of win-win ones. Finally, lots of experiments confirm that our negotiation model outperforms the existing models developed recently. And the experiments also show our model is stable and efficient in finding fair win-win outcomes, which is seldom solved in the existing models.

Original languageEnglish
Pages (from-to)577-626
Number of pages50
JournalComputational Intelligence
Issue number4
Early online date3 Jul 2012
Publication statusPublished - Nov 2013


  • agent
  • automated negotiation
  • e-business
  • evolutionary computing
  • multiattribute decision making


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