广东工业大学学报 ›› 2006, Vol. 23 ›› Issue (2): 1-11.

• 综合研究 •    下一篇

全局优化的了望算法

  

  1. 广东工业大学自动化学院; 浙江大学工业控制技术国家重点实验室; 浙江大学工业控制技术国家重点实验室 广东广州510090; 浙江杭州310027;
  • 出版日期:2006-04-06 发布日期:2006-04-06

Outlook Algorithm for Global Optimization

  1. (1.Faculty of Automation,Guangdong University of Technology,Guangzhou 510090, China2.National Laboratory of Industrial Control Technology,Zhejiang University, Hangzhou 310027,China)
  • Online:2006-04-06 Published:2006-04-06

摘要: 提出求解全局优化问题的了望算法.了望算法利用了望技术确定群山最高点的常识,通过了望管理机制、了望点产生策略、局部问题构造与求解机制,能在较短的时间内求解全局优化问题.大量的测试表明,了望算法具有较高的收敛率和较强的获得问题全部解的能力,对初始点几乎没有依赖,参数选择简单.了望算法能够保证在迭代过程中迭代点的质量逐步变好,所提出的三层次记忆机制极大地提高了望算法的收敛速度.大量的对比测试也表明,在收敛率和全局搜索能力等方面了望算法较遗传算法有一定的优势,且在大多数情况下了望算法耗时较少.由于了望算法是根据人类的高级行为智能和推理智能提出的一种智能算法,它为解决全局优化问题开辟了一条新的途径. 

关键词: 了望算法; 全局优化; 智能算法;

Abstract: Outlook algorithm is presented to solve global optimization problems in this paper.Based on common knowledge that one decides the highest point of mountains by outlook,by employing supervision mechanism of outlook,strategies of generating outlook points and mechanisms of constructing and solving local problems,outlook algorithm can solve any global optimization problem in a relatively short time.A large number of tests show that outlook algorithm is of higher convergence ratio,stronger capacity to obtain all solutions of global optimization problems,little dependence on initial solution and simplicity in deciding its control parameters.It can be ensured that the quality of iterative points will gradually improve in the iterative process of outlook algorithm.The three-level memory mechanism of outlook algorithm greatly increases its convergence rate.A large number of contrast tests also show that outlook algorithm has advantage over genetic algorithm in convergence ratio and capacity of global search,and spends less time than genetic algorithm in most cases.Since outlook algorithm simulates human behavioral and inferential intelligence,it exploits a brand new way to solve global optimization problems. 

Key words: outlook algorithm; global optimization; intelligent algorithm;

[1] 蔡延光,钱积新,孙优贤.  带时间窗的多重运输调度问题的自适应Tabu Search算法[J]. 系统工程理论与实践. 2000(12)

[2] 蔡延光,钱积新,孙优贤.  多重运输调度问题的模拟退火算法[J]. 系统工程理论与实践. 1998(10)

[3] 蔡延光,钱积新,孙优贤.  多重运输调度问题的遗传算法及遗传局部搜索[J]. 系统工程理论与实践. 1997(12)

[1] 王凌著.智能优化算法及其应用[M]. 清华大学出版社, 2001

[1] J. J. Hopfield,D. W. Tank.  “Neural” computation of decisions in optimization problems[J] ,1985
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