一种文化算法优化
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TP391

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汽车噪声振动和安全技术国家重点实验室开放基金项目(NVHSKL-201601)。


An optimization of cultural algorithm
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    摘要:

    工程中复杂的优化问题很难获得其解析解,通过数值计算方法去获取数值解容易陷入局部最优解。为提高求解高维问题数值最优解的速度和准确性,在传统文化算法基础上将种群分为精英群体和普通群体,分别按照不同的方式进化并对种群做初始化优化,通过MATLAB编程用实例分别对优化前后的算法进行仿真。实验表明,优化后较优化前在速度上有较大的提升,进行初始化改进的文化算法在高维优化问题中能更快、更准确地逼近最优解,为求解复杂的问题提供了一种新的参考方法。

    Abstract:

    It's difficult to obtain the analytic solution of complicated optimization problems in engineering. To try to get numerical solution with numerical computation method is easy to get local optimal solution instead. In order to improve the speed and accuracy of numerical optimal solution to high-dimensional problems, the population is divided into intelligent population and common population on the basis of traditional culture algorithm, and they are initially optimized according to different evolving ways respectively. Furthermore, simulation of practical examples by MATLAB program is carried out. The results show that the speed is greatly improved after optimization and the cultural algorithm with initialized improvement can approximate the optimal solution faster and more accurately in high-dimensional optimization problems. The optimized cultural algorithm provides a new reference for practical engineering problem.

    参考文献
    [1] 黎明,江乐旗,陈昊.基于文化算法的无人飞行器航迹规划[J]. 模式识别与人工智能,2017,30(2):152-161. LI Ming, JIANG Leqi, CHEN Hao. Route planning method for unmanned aerial vehicle based on cultural algorithm[J]. Pattern Recognition and Artificial Intelligence, 2017, 30(2): 152-161. (in Chinese)
    [2] 朱志洁,张宏伟,王春明.基于人工蜂群算法优化支持向量机的采场底板破坏深度预测[J].重庆大学学报,2015,38(6):37-43. ZHU Zhijie, ZHANG Hongwei, WANG Chunming. Prediction of floor damaged depth in working area based on support vector machine and artificial bee colony algorithm[J]. Journal of Chongqing University, 2015, 38(6): 37-43. (in Chinese)
    [3] 刘新平,吴晓玲,张艳艳.基于文化遗传算法的水浴温度模糊控制器设计[J].计算机测量与控制,2015,23(10):3409-3411+3424. LIU Xinping, WU Xiaoling, ZHANG Yanyan. Fuzzy temperature controller design for Water-bath based cultural genetic algorithm[J]. Computer Measurement & Control, 2015, 23(10): 3409-3411+3424. (in Chinese)
    [4] Cheng M Y, Prayogo D. Symbiotic organism search: A new metaheuristic optimization algorithm[J]. Computers Structures, 2014, 139: 98-112.
    [5] Reynolds R G. An introduction to cultural algorithms[C]//Proceedings of the Third Annual Conference on Evolutionary Programming, San Diego, 1994. San Diego:[s.n], 1994: 131-139.
    [6] CMcioglu P. Backtracking search optimization algorithm for numerical optimization problem[J]. Applied Mathematics & Computation, 2013, 219(15): 8121-8144.
    [7] 姚新,陈国良,徐惠敏,等.进化算法研究进展[J].计算机学报,1995,18(9):694-706. YAO Xin, CHEN Guoliang, XU Huiming, et al. A survey of evolutionary algorithms[J]. Chinese Journal of Computers, 1995,18(9): 694-706. (in Chinese)
    [8] 黄海燕,顾幸生.基于文化算法的神经网络及其在建模中的应用[J].控制与决策,2008,23(4):477-480. HUANG Haiyan, GU Xingsheng. Neural network based on cultural algorithms and its application on modeling[J]. Control and Decision, 2008, 23(4): 477-480. (in Chinese)
    [9] Engelbrecht A P. Computational intelligence: An introduction[C]//Internet of Things. 2nd ed.[S.l.]: IEEE, 2007: 675-680.
    [10] 刘纯青.文化算法及其应用研究[D].哈尔滨:哈尔滨工程大学,2007. LIU Chunqing. Research on culture algorithm and their application[D]. Harbin: Harbin Engineering University, 2007. (in Chinese)
    [11] Yang K, Maginu K, Nomura H. Cultural algorithm-based quantum-behaved particle swarm optimization[J]. International Journal of Computer Mathematics, 2010, 87(10): 2143-2157.
    [12] Ali M Z, Reynolds R G. Cultural algorithms: A Tabu search approach for the optimization of engineering design problems[J]. Soft Computing, 2014, 18(8): 1631-1644.
    [13] Yang K, Maginu K, Nomura H. Cultural algorithm-based quantum-behaved particle swarm optimization[M].[S.l.]: Taylor & Francis, Inc, 2010.
    [14] Akay B, Karaboga D. A modified artificical bee colony algorithm for real-parameter optimization[J]. Information Sciences, 2012, 192(1): 120-142.
    [15] 李江云,汪慧,盛旺,等.用遗传算法进行RFD装置优化设计[J].重庆大学学报,2016,39(3):13-20. LI Jiangyun, WANG Hui, SHENG Wang, et al. Optimizition design of RFD set based on genetic algorithm[J]. Journal of Chongqing University, 2016, 39(3): 13-20. (in Chinese)
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谭涛,邓兆祥,舒红宇,杨金歌.一种文化算法优化[J].重庆大学学报,2018,41(4):29-34.

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  • 收稿日期:2017-11-06
  • 在线发布日期: 2018-05-06
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