Population Distributions in Biogeography-Based Optimization Algorithms with Elitism

被引:34
|
作者
Simon, Dan [1 ]
Ergezer, Mehmet [1 ]
Du, Dawei [1 ]
机构
[1] Cleveland State Univ, Dept Elect & Comp Engn, Cleveland, OH 44115 USA
关键词
biogeography-based optimization; evolutionary algorithms; probability; combinatorics; Markov analysis;
D O I
10.1109/ICSMC.2009.5346058
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Biogeography-based optimization (BBO) is an evolutionary algorithm that is based on the science of biogeography. Biogeography is the study of the geographical distribution of organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration between islands. This paper develops a Markov analysis of BBO, including the option of elitism. Our analysis gives the probability of BBO convergence to each possible population distribution for a given problem. We compare our BBO Markov analysis with a similar genetic algorithm (GA) Markov analysis. Analytical comparisons on three simple problems show that with high mutation rates the performance of GAs and BBO is similar, but with low mutation rates BBO outperforms GAs. Our analysis also shows that elitism is not necessary for all problems, but for some problems it can significantly improve performance.
引用
收藏
页码:991 / 996
页数:6
相关论文
共 50 条
  • [21] A Hybrid of Firefly and Biogeography-Based Optimization Algorithms for Optimal Design of Steel Frames
    Farrokh Ghatte, Hamid
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2021, 46 (05) : 4703 - 4717
  • [22] Heuristic Crossover Based on Biogeography-based Optimization
    Feng, Mengqing
    PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, INFORMATION AND MECHANICAL ENGINEERING (EMIM 2017), 2017, 76 : 336 - 341
  • [23] Complex System Optimization Using Biogeography-Based Optimization
    Du, Dawei
    Simon, Dan
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
  • [24] Accelerated biogeography-based optimization with neighborhood search for optimization
    Lohokare, M. R.
    Pattnaik, S. S.
    Panigrahi, B. K.
    Das, Sanjoy
    APPLIED SOFT COMPUTING, 2013, 13 (05) : 2318 - 2342
  • [25] Constrained Optimization based on Epsilon Constrained Biogeography-Based Optimization
    Bi, Xiaojun
    Wang, Jue
    2012 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL 2, 2012, : 369 - 372
  • [26] Statistical Mechanics Approximation of Biogeography-Based Optimization
    Ma, Haiping
    Simon, Dan
    Fei, Minrui
    EVOLUTIONARY COMPUTATION, 2016, 24 (03) : 427 - 458
  • [27] Biogeography-based optimization based on population competition strategy for solving the substation location problem
    Li, Ling-Ling
    Yang, Yan-Fang
    Wang, Ching-Hsin
    Lin, Kuo-Ping
    EXPERT SYSTEMS WITH APPLICATIONS, 2018, 97 : 290 - 302
  • [28] Handling Multiple Objectives with Biogeography-based Optimization
    Hai-Ping Ma Xie-Yong Ruan Zhang-Xin Pan Department of Physics and Electrical Engineering
    International Journal of Automation and Computing, 2012, (01) : 30 - 36
  • [29] Separation of Fire Images with Biogeography-Based Optimization
    Toptas, Buket
    Hanbay, Davut
    Yeroglu, Celaleddin
    2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA PROCESSING (IDAP), 2018,
  • [30] Hybrid Biogeography-Based Optimization for Integer Programming
    Wang, Zhi-Cheng
    Wu, Xiao-Bei
    SCIENTIFIC WORLD JOURNAL, 2014,