Adaptive Flower Pollination Algorithm with Simulated Annealing Mechanism
Computer Science

Computer Science ›› 2018, Vol. 45 ›› Issue (11): 231-237.doi: 10.11896／j.issn.1002-137X.2018.11.036

• Artificial Intelligence • Previous Articles     Next Articles

Adaptive Flower Pollination Algorithm with Simulated Annealing Mechanism

LIU Jing-sen1,2, LIU Li2, LI Yu3   

  1. (Institute of Intelligent Networks System,Henan University,Kaifeng,Henan 475004,China)1
    (College of Software,Henan University,Kaifeng,Henan 475004,China)2
    (Institute of Management Science and Engineering,Henan University,Kaifeng,Henan 475004,China)3
  • Received:2017-10-27 Published:2019-02-25

PDF (PC)

852

Abstract: Aiming at the shortages of basic flower pollination algorithm,in order to improve the convergence rate and optimization accuracy of the algorithm,this paper proposed an adaptive flower pollination algorithm fusing simulated annealing mechanism and dynamically adjusting the global step length and local reproduction probability according to the iterative evolution.Firstly,the scaling factor of the deformed exponential function is used to control step length in the global pollination of the basic algorithm,so that the individual of flower can be adaptively updated with the number of iterations.Then,through combining Rayleigh distribution function and the number of iterations,the factors of multiplication probability are improved,thus avoiding the precocious convergence and making the solution close to the optimal solution in the later stage.Finally,a simulated annealing cooling operation is incorporated into the improved flower pollination algorithm,which not only increases the diversity of population,but also improves the overall performance of algorithm.The simulation results show that the algorithm has faster convergence speed and higher convergence precision,and the optimization performance of the proposed algorithm is improved.

Key words: Flower pollination algorithm, Local multiplication probability, Rayleigh distribution function, Simulated annealing operation, Step size scaling factor

CLC Number: 

  • TP301.6
[1]EBERHART R,KENNEDY J.A new optimizer using particle swarm theory[C]∥Proceedings of the Sixth International Symposium on Micro Machine and Human Science.1995:39-43.
[2]KENNEDY J,EBERHART R.Particle swarm optimization [C]∥ IEEE International Conference on Neural Networks,1995.IEEE,2002:1942-1948.
[3]GOLDBERG D E.Genetic Algorithm in Search Optimization and Machine Learning [J].Addison Wesley,1989,13(7):2104-2116.
[4]YANG X S,DEB S.Cuckoo Search via Lévy flights [C]∥World Congress on Nature & Biologically Inspired Computing(NaBIC 2009).IEEE,2010:210-214.
[5]YANG X S.A New Metaheuristic Bat-Inspired Algorithm[J].Computer Knowledge & Technology,2010,284:65-74.
[6]YANG X S.Flower Pollination Algorithm for Global Optimization[C]∥International Conference on Unconventional Computation and Natural Computation.Springer-Verlag,2012:240-249.
[7]HAKLI H,UGˇUZ H.A novel particle swarm optimization algo- rithm with Levy flight[J].Applied Soft Computing,2014,23(5):333-345.
[8]YANG X S,KARAMANOGLU M,HE X.Multi-objective Flower Algorithm for Optimization[J].Procedia Computer Scien-ce,2013,18(1):861-868.
[9]RODRIGUES D,YANG X S,SOUZA A N D,et al.Binary Flower Pollination Algorithm and Its Application to Feature Selection[M]∥Recent Advances in Swarm Intelligence and Evolutionary Computation.Springer International Publishing,2015:85-100.
[10]DUBEY H M,PANDIT M,PANIGRAHI B K.Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch[J].Renewable Energy,2015,83:188-202.
[11]JENSI R,JIJI G W.Hybrid data clustering approach using K- Means and Flower Pollination Algorithm[J].Computer Science,2015,2(2):15-25.
[12]JIAO Q L,XU D,LI C.Product Disassembly Sequence Planning Based on Flower Pollination Algorithm[J].Computer Integrated Manufacturing Systems,2016,22(12):2791-2799.(in Chinese)
焦庆龙,徐达,李闯.基于花朵授粉算法的产品拆卸序列规划[J].计算机集成制造系统,2016,22(12):2791-2799.
[13]BENSOUYAD M,SAIDOUNI D E.A discrete flower pollina- tion algorithm for graph coloring problem[C]∥International Conference on Cybernetics.IEEE,2015:151-155.
[14]ALAM D F,YOUSRI D A,ETEIBA M B.Flower Pollination Algorithm based solar PV parameter estimation[J].Energy Conversion & Management,2015,101:410-422.
[15]EL-HENAWY I,ABDEL-RAOUF O,ABDEL-BASET M.A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems[J].International Journal of Applied Operational Research,2014,4(2):1-13.
[16]WANG R,ZHOU Y.Flower Pollination Algorithm with Dimension by Dimension Improvement [J].Mathematical Problems in Engineering,2014,2014(4):1-9.
[17]KN L,RAVINDHRANATHREDDY B,SURYAKALAVATHI M.Shrinkage of Active Power Loss by Hybridization of Flower Pollination Algorithm with Chaotic Harmony Search Algorithm[J].Control Theory & Informatics,2014,4(8):31-38.
[18]NABIL E.A Modified Flower Pollination Algorithm for Global Optimization[J].Expert Systems with Applications,2016,57:192-203.
[19]XIAO H H,WAN C X,DUAN Y M,et al.Flower pollination algorithm based on simulated annealing[J].Journal of Computer Applications,2015,35(4):1062-1066.(in Chinese)
肖辉辉,万常选,段艳明,等.基于模拟退火的花朵授粉优化算法[J].计算机应用,2015,35(4):1062-1066.
[20]LI R Y,DAI R W.An adaptive step cuckoo search algorithm [J].Computer Science,2017,44(5):235-240.(in Chinese)
李荣雨,戴睿闻.自适应步长布谷鸟搜索算法[J].计算机科学,2017,44(5):235-240.
[21]YANG R L,GU J F.A Efficient Global Optimization Algorithm for Simulated Annealing [J].Systems Engineering-Theory & Practice,1997,17(5):29-35.(in Chinese)
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.
[22]LIU H B,WANG X K,TAN G Z.Convergence Analysis of Particle Swarm Optimization Algorithm and Improved Chaos Algorithm [J].Control and Decision,2006,21(6):636-640.(in Chinese)
刘洪波,王秀坤,谭国真.粒子群优化算法的收敛性分析及其混沌改进算法[J].控制与决策,2006,21(6):636-640.
[23]LI Z Y,MA L,ZHANG H Z.Analysis of Bats Algorithm Convergence[J].Mathematics Practice and Understanding,2013,43(12):182-190.(in Chinese)
李枝勇,马良,张惠珍.蝙蝠算法收敛性分析[J].数学的实践与认识,2013,43(12):182-190.[24]WANG R,ZHOU Y,ZHAO C,et al.A hybrid flower pollination algorithm based modified randomized location for multi-thre-shold medical image segmentation[J].Bio-medical materials and engineering,2015,26 Suppl 1(s1):S1345.
[25]WANG H,OUYANG H B,GAO L Q.An Improved Global Particle Swarm Optimization Algorithm [J].Control and Decision,2016,31(7):1161-1168.(in Chinese)
王皓,欧阳海滨,高立群.一种改进的全局粒子群优化算法[J].控制与决策,2016,31(7):1161-1168.
[26]MENG X B,GAO X Z,LIU Y,et al.A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization [J].Expert Systems with Applications,2015,42(17／18):6350-6364.
[1] SHAO Zi-hao, YANG Shi-yu, MA Guo-jie. Foundation of Indoor Information Services:A Survey of Low-cost Localization Techniques [J]. Computer Science, 2022, 49(9): 228-235.
[2] SUN Gang, WU Jiang-jiang, CHEN Hao, LI Jun, XU Shi-yuan. Hidden Preference-based Multi-objective Evolutionary Algorithm Based on Chebyshev Distance [J]. Computer Science, 2022, 49(6): 297-304.
[3] LI Dan-dan, WU Yu-xiang, ZHU Cong-cong, LI Zhong-kang. Improved Sparrow Search Algorithm Based on A Variety of Improved Strategies [J]. Computer Science, 2022, 49(6A): 217-222.
[4] HU Cong, HE Xiao-hui, SHAO Fa-ming, ZHANG Yan-wu, LU Guan-lin, WANG Jin-kang. Traffic Sign Detection Based on MSERs and SVM [J]. Computer Science, 2022, 49(6A): 325-330.
[5] YANG Jian-nan, ZHANG Fan. Classification Method for Small Crops Combining Dual Attention Mechanisms and Hierarchical Network Structure [J]. Computer Science, 2022, 49(6A): 353-357.
[6] ZHANG Jia-hao, LIU Feng, QI Jia-yin. Lightweight Micro-expression Recognition Architecture Based on Bottleneck Transformer [J]. Computer Science, 2022, 49(6A): 370-377.
[7] WANG Fang-hong, FAN Xing-gang, YANG Jing-jing, ZHOU Jie, WANG De-en. Strong Barrier Construction Algorithm Based on Adjustment of Directional Sensing Area [J]. Computer Science, 2022, 49(6A): 612-618.
[8] ZHANG Zhi-long, SHI Xian-jun, QIN Yu-feng. Diagnosis Strategy Optimization Method Based on Improved Quasi Depth Algorithm [J]. Computer Science, 2022, 49(6A): 729-732.
[9] GAO Yuan-hao, LUO Xiao-qing, ZHANG Zhan-cheng. Infrared and Visible Image Fusion Based on Feature Separation [J]. Computer Science, 2022, 49(5): 58-63.
[10] LIU Yang, LI Fan-zhang. Fiber Bundle Meta-learning Algorithm Based on Variational Bayes [J]. Computer Science, 2022, 49(3): 225-231.
[11] QIAO Jie, CAI Rui-chu, HAO Zhi-feng. Mining Causality via Information Bottleneck [J]. Computer Science, 2022, 49(2): 198-203.
[12] ZHAO Xue-lei, JI Xin-sheng, LIU Shu-xin, LI Ying-le, LI Hai-tao. Link Prediction Method for Directed Networks Based on Path Connection Strength [J]. Computer Science, 2022, 49(2): 216-222.
[13] WEI Xin, FENG Feng. Optimization of Empire Competition Algorithm Based on Gauss-Cauchy Mutation [J]. Computer Science, 2021, 48(11A): 142-146.
[14] WANG You-wei, ZHU Chen, ZHU Jian-ming, LI Yang, FENG Li-zhou, LIU Jiang-chun. User Interest Dictionary and LSTM Based Method for Personalized Emotion Classification [J]. Computer Science, 2021, 48(11A): 251-257.
[15] XIAO Man, LI Wei-dong. Semi-online Algorithms for Mixed Ring with Two Nodes [J]. Computer Science, 2021, 48(11A): 441-445.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.