A Genetic Algorithm Based on Metropolis Rule and Its Application in Multi-Lateral Multi-Issue Negotiation

LI Jian; JING Bo; YANG Yi-xian

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A Genetic Algorithm Based on Metropolis Rule and Its Application in Multi-Lateral Multi-Issue Negotiation

更新时间：2025-07-16

- A Genetic Algorithm Based on Metropolis Rule and Its Application in Multi-Lateral Multi-Issue Negotiation
- Acta Electronica Sinica Vol. 37, Issue 5, Pages: 1037-1040(2009)
- 作者机构：
  
  1. 北京邮电大学网络与交换技术国家重点实验室信息安全中心,北京,100876
  2. 北京应用气象研究所计算机室,北京,100029
  3. 北京邮电大学网络与交换技术国家重点实验室信息安全中心北京,100876
  4. 北京应用气象研究所计算机室北京,100029
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN301
- Published：2009
- 稿件说明：
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LI Jian, JING Bo, YANG Yi-xian. A Genetic Algorithm Based on Metropolis Rule and Its Application in Multi-Lateral Multi-Issue Negotiation[J]. Acta Electronica Sinica, 2009, 37(5): 1037-1040.
DOI：

LI Jian, JING Bo, YANG Yi-xian. A Genetic Algorithm Based on Metropolis Rule and Its Application in Multi-Lateral Multi-Issue Negotiation[J]. Acta Electronica Sinica, 2009, 37(5): 1037-1040. DOI：

摘要

为了使得基于智能体电子商务中协商智能体最大限度地达到协商的满意解

甚至最优解

并且提高协商的效率

提出将基于Metropolis准则的遗传算法应用于基于智能体电子商务的多边多议题同时出价的协商当中.经过1000次的实验数据表明

简单遗传算法平均需要155次才能达到协商的最优解

而基于Metropolis准则的遗传算法平均需要76次就达到协商的最优解.这个结果表明

基于Metropolis准则的遗传算法可以使得多边多议题协商中的智能体高效达到协商的最优解.

Abstract

To make the negotiation agents gain satisfying result and negotiate more efficiently in multi-agent based e-commerce

a genetic algorithm based on metropolis rule is presented and the algorithm is applied in multi-lateral multi-issue simultaneous bidding negotiation.After 1000 times of experiments

simple genetic algorithm averagely needs 155 runs to gain the satisfying result

while the genetic algorithm based on metropolis rule averagely needs 76 runs to gain the satisfying result.The experimental result show the genetic algorithm based on metropolis rule can gain the optimal negotiate result more efficiently in multi-literal multi-issue negotiation.

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