动态改变邻域空间和搜索步的自由搜索算法

doi:10.3969/j.issn.1001-2400.2010.04.028

Abstract

Abstract:

To overcome the problem of population-based optimisation algorithms-free search (FS) to find the best solution with the low efficient later stage, especially multi-dimensional search space, FS with the variable neighbourhood and step method is proposed. The previous neighbourhood space and step do not change much in searching for the overall situation and change relatively greatly in the later stage in local exploration by the algorithm. The methods for the varying neighbourhood and step are given and simulation results with four traditional functions show that the algorithm has a better probability of finding the global optimum and mean best value, with quick convergence and high precision, especially for the multi-dimensional and multimodal function.

Key words: free search, global optimization, neighbourhood space, algorithms, search step

LI Tuan-jie;CAO Yu-yan;SUN Guo-ding. Free search algorithm with the variable neighbourhood and step[J].J4, 2010, 37(4): 737-742.

References

[1] Holland J H. Adaptation in Natural and Artificial Systems[M]. Cambridge: MIT Press, 1992.
[2] Alberto C, Maniezzo D. Distributed Optimization by Ant Colonies [C]//Proc of the First European Conf on Artificial Life. Paris: Elsevier Publishing, 1991:134-142.
[3] 寇晓丽, 刘三阳. 一种求解连续优化的蚁群混合算法[J]. 西安电子科技大学学报, 2006, 33(5): 745-747.
Kou Xiaoli, Liu Sanyang. Hybrid Algorithm Based on Ant Colony Optimization in Continuous Space Optimization [J]. Journal of Xidian University, 2006, 33(5): 745-747.
[4] Kennedy J, Eberhart R. Partical Swarm Optimization [C]//IEEE Int Conf on Neural Networks. Piscataway: IEEE Service Center, 1995: 1942-1948.
[5] Shi Y, Eberhart R. A Modified Particle Swarm Optimizer [C]//IEEE World Conf on Computational Intelligence. Piscataway: IEEE Press, 1998: 69-73.
[6] 赵俊, 陈建军. 混沌粒子群优化的模糊神经PID控制器设计[J]. 西安电子科技大学学报, 2008, 35(5): 54-59.
Zhao Jun, Chen Jianjun. Design of the Fuzzy Neural PID Controller Based on Hybrid PSO[J]. Journal of Xidian University, 2008, 35(5): 54-59.
[7] 韩江洪, 李正荣, 魏振春. 一种自适应粒子群优化算法及其仿真研究[J]. 系统仿真学报, 2006, 18(10): 2969-2971.
Han Jianghong, Li Zhengrong, Wei Zhenchun. Adaptive Particle Swarm Optimization Algorithm and Simulation[J]. J of System Simulation, 2006,18(10): 2969-2971.
[8] 张顶学, 关治洪, 刘新芝. 一种动态改变惯性权重的自适应粒子群算法[J]. 控制与决策, 2008, 23(11): 1253-1257.
Zhang Dingxue, Guan Zhihong, Liu Xinzhi. Adaptive Particle Swarm Optimization Algorithm with Dynamically Change Inertia Weight[J]. Control and Decision, 2008, 23(11): 1253-1257.
[9] 罗辞勇, 陈民轴. 适应性粒子群寻优算法[J]. 控制与决策, 2008, 23(10): 1135-1138.
Luo Ciyong, Chen Minzhou. Adaptive Particle Swarm Optimization Algorithm[J]. Control and Decision, 2008, 23(10): 1135-1138.
[10] Penev K, Littlefair G. Free Search—a Comparative Analysis[J]. Information Sciences, 2005,172(1-2): 173-193.
[11] 周晖, 徐晨, 邵世煌, 等. 自适应搜索优化算法[J]. 计算机科学, 2008, 35(10): 188-191.
Zhou Hui, Xu Chen, Shao Shihuang, et al. Adaptive Free Search Algorithm[J]. Computer Science, 2008, 35(10): 188-191.
[12] 周晖, 李丹美, 邵世煌, 等. 一种新的群集智能优化及其改进研究[J]. 系统工程与电子技术, 2008, 30(2): 337-340.
Zhou Hui, Li Danmei, Shao Shihuang, et al. Novel Swarm Intelligence Algorithm and Its Improvement[J]. Systems Engineering and Electronics, 2008, 30(2): 337-340.

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Free search algorithm with the variable neighbourhood and step

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