吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (增刊1): 173-178.

• 论文 • 上一篇    下一篇

求解约束多目标优化问题的Agent进化算法

丁辉, 李宏光   

  1. 北京化工大学信息科学与技术学院, 北京 100029
  • 收稿日期:2011-02-14 出版日期:2011-09-01 发布日期:2011-09-01
  • 通讯作者: 李宏光(1963 ),男,教授.博士.研究方向:智能控制.E-mail: lihg@mail.huct.edu.cn. E-mail: lihg@mail.huct.edu.cn
  • 作者简介:丁辉(1985 ),女,硕士.研究方向:智能控制.E-mail:eppie1018@yahoo.com.cn.
  • 基金资助:

    北京市重点学科基金项目(XK100100435)

Agent-based evolutionary approach towards solving constrained multi-objective optimization problems

DING Hui, LI Hong-guang   

  1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2011-02-14 Online:2011-09-01 Published:2011-09-01

摘要:

针对目前Agent进化算法难以处理含约束多目标优化的问题,把标准化的约束违反程度作为一个优化目标,从而对Agent所具有的能量产生影响;设置了最优解集和最优可行解集两个外部存储集,以便在寻优过程中保持Agent群体的多样性;对可行解以及约束违反程度小的Agent进行局部爬山操作,更加有利于寻找最优可行解。将算法应用于数值实例和焊接梁的设计优化问题中,表明该算法既保持了种群的多样性,又能够快速收敛。

关键词: 人工智能, 进化算法, 约束多目标优化, 智能体

Abstract:

In regard to constrained multi-objective optimization problems which are traditionally intractable by means of agent based evolutionary algorithm,the normalized violation degrees of the constraints were considered as additional objectives able to influence the energy of the agents.Additionally,two external archives,an optimal solution set and an optimal feasible solution set were available to maintain the diversity of population.It is efficient to achieve the optimal solutions by carrying out climbing operations on both candidate solutions and agents with small violation degrees.Case studies consisting in test functions and optimal design of welded beams show that the proposed algorithm not only keep the diversity of population but also converge to the optimal fronts quickly.

Key words: artificial intelligence, evolutionary algorithm, constrained multi-objective optimization, agents

中图分类号: 

  • TP3


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