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A novel adaptive mutative scale optimization algorithm based on chaos genetic method and its optimization efficiency evaluation 被引量:5

A novel adaptive mutative scale optimization algorithm based on chaos genetic method and its optimization efficiency evaluation
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摘要 By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm. By combing the properties of chaos optimization method and genetic algorithm, an adaptive mutative scale chaos genetic algorithm (AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1, 1]. Some measures in the optimization algorithm, such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline, were taken to ensure its speediness and veracity in seeking the optimization process. The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision. Furthermore, the average truncated generations, the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally. It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm.
出处 《Journal of Central South University》 SCIE EI CAS 2012年第9期2554-2560,共7页 中南大学学报(英文版)
基金 Project(60874114) supported by the National Natural Science Foundation of China
关键词 chaos genetic optimization algorithm CHAOS genetic algorithm optimization efficiency 混沌优化方法 变尺度方法 优化效率 优化算法 遗传方法 自适应 基础 评价
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  • 1郝柏林.从抛物线谈起-混沌动力学引论[M].上海科技教育出版社,1995.1-20.
  • 2杨若黎,顾基发.一种高效的模拟退火全局优化算法[J].系统工程理论与实践,1997,17(5):29-35. 被引量:101
  • 3Chen L,中日青年国际学术讨论会论文集,1995年
  • 4卢侃,混沌动力学,1990年
  • 5郝柏林,从抛物线谈起.混沌动力学引论,1995年,1页
  • 6陈国良,遗传算法及其应用,1996年,5页
  • 7Changkyu Choi,Ju-Jang Lee.Chaotic local search algorithm[J].Artificial Life and Robotics.1998(1)
  • 8C. Choi,,J. Lee.Chaotic local search algorithm[].Artificial Life.1998
  • 9D. Cvijovic,J. Kilnowski.Taboo search: an approach to the multiple minima problem[].Science.1995
  • 10WANG Ling 1,ZHENG Da-zhong 1,LIN Qing-sheng 2 (1.Dept.of Automation, Tsinghua University, Beijing 100084,2.Dept.Of Physics,BUAA 100083).Survey on Chaotic Optimization Methods[].Computing Technology and Automation.2001

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