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Home > Archive>Volume 23, Issue 11, 2012 >2987-2999. DOI:10.3724/SP.J.1001.2012.04299
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Concurrent Negotiation of Relative Issues Based on Genetic Algorithm
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    Abstract:

    The concurrent negotiation based on genetic algorithm has special advantages in e-commerce applications. But, the relativity of issues and the dynamic weights of issues are not taken into account in existing research. Thus, this paper proposes a solution to these problems by grouping the issues and adapting the dynamic weights, according to data mining from history resources. The concurrent negotiation model of relative issues is described in detail, including the formal definition of the model, the design of concurrent negotiation algorithm, and the update scheme of dynamic weights. The experimental results show that the model can meet the requirements of different negotiations, solve the issues’ relativity problem in the process of negotiation, and improve the negotiation efficiency.

    Reference
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    [12] Shen JH, Yu XJ, Li SZ, Li J. A bilateral multi-issue negotiation protocol based on adaptive genetic algorithm. In: Proc. of theMASS 2009. Danvers, Piscataway: IEEE Computer Society, 2009. 1-4. [doi: 10.1109/ICMSS.2009.5303304]
    [13] Sim KM, Guo YY, Shi BY. BLGAN: Bayesian learning and genetic algorithm for supporting negotiation with incompleteinformation. IEEE Trans. on Systems, Man, and Cybernetics, 2009,39(1):198-211. [doi: 10.1109/TSMCB.2008.2004501]
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甘早斌,朱春喜,马尧,鲁宏伟.基于遗传算法的关联议题并发谈判.软件学报,2012,23(11):2987-2999

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History
  • Received:June 15,2012
  • Revised:August 15,2012
  • Online: October 31,2012
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