Enhancing the performance of biogeography-based optimization using polyphyletic migration operator and orthogonal learning

Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess local exploitation ability but...

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Published in:	Computers & operations research Vol. 41; pp. 125 - 139
Main Authors:	Xiong, Guojiang, Shi, Dongyuan, Duan, Xianzhong
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.01.2014 Elsevier Pergamon Press Inc
Subjects:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Biogeography Biogeography-based optimization Computer science; control theory; systems Design of experiments Exact sciences and technology Experimental design Global numerical optimization Mathematical analysis Mathematical models Mathematical problems Mathematics Migration Operations research Operators Optimization algorithms Orthogonal experimental design (OED) Orthogonal learning Performance enhancement Polyphyletic migration operator Probability and statistics Sciences and techniques of general use Searching Statistics Strategy Studies Theoretical computing Vector space Global numerical optimization Orthogonal learning Biogeography-based optimization Orthogonal experimental design (OED) Polyphyletic migration operator Orthogonal design Probabilistic approach Useful information Evolutionary algorithm Migration Biogeography Global optimum Information retrieval Experimental result Experimental design Reasoning Heuristic method Convergence rate Defect Swarm intelligence Learning algorithm Numerical convergence
ISSN:	0305-0548, 1873-765X, 0305-0548
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Abstract	Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess local exploitation ability but lack global exploration ability. To remedy the defect and enhance the performance of BBO, an enhanced BBO variant, called POLBBO, is developed in this paper. In POLBBO, a proposed efficient operator named polyphyletic migration operator can formally utilize as many as four individuals’ features to construct a new solution vector. This operator cannot only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is employed. The OL strategy can quickly discover more useful information from the search experiences and efficiently utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. The proposed POLBBO is verified on a set of 24 benchmark functions with diverse complexities, and is compared with the basic BBO, five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms. The experimental results and comparisons demonstrate that the polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly in terms of the quality of the final solutions and the convergence rate. •An enhanced BBO variant (POLBBO) is developed for solving global numerical optimization problems.•A polyphyletic migration operator is proposed to generate new features from more promising areas in the search space.•An OL strategy is employed to provide a systematic reasoning method to guide the search directions of POLBBO.•The polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly.•Five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms are employed to compare.
AbstractList	Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess local exploitation ability but lack global exploration ability. To remedy the defect and enhance the performance of BBO, an enhanced BBO variant, called POLBBO, is developed in this paper. In POLBBO, a proposed efficient operator named polyphyletic migration operator can formally utilize as many as four individuals' features to construct a new solution vector. This operator cannot only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is employed. The OL strategy can quickly discover more useful information from the search experiences and efficiently utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. The proposed POLBBO is verified on a set of 24 benchmark functions with diverse complexities, and is compared with the basic BBO, five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms. The experimental results and comparisons demonstrate that the polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly in terms of the quality of the final solutions and the convergence rate. Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess local exploitation ability but lack global exploration ability. To remedy the defect and enhance the performance of BBO, an enhanced BBO variant, called POLBBO, is developed in this paper. In POLBBO, a proposed efficient operator named polyphyletic migration operator can formally utilize as many as four individuals' features to construct a new solution vector. This operator cannot only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is employed. The OL strategy can quickly discover more useful information from the search experiences and efficiently utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. The proposed POLBBO is verified on a set of 24 benchmark functions with diverse complexities, and is compared with the basic BBO, five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms. The experimental results and comparisons demonstrate that the polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly in terms of the quality of the final solutions and the convergence rate. [PUBLICATION ABSTRACT] Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and engineering problems. However, its direct-copying-based migration and random mutation operators make BBO possess local exploitation ability but lack global exploration ability. To remedy the defect and enhance the performance of BBO, an enhanced BBO variant, called POLBBO, is developed in this paper. In POLBBO, a proposed efficient operator named polyphyletic migration operator can formally utilize as many as four individuals’ features to construct a new solution vector. This operator cannot only generate new features from more promising areas in the search space, but also effectively increase the population diversity. On the other hand, an orthogonal learning (OL) strategy based on orthogonal experimental design is employed. The OL strategy can quickly discover more useful information from the search experiences and efficiently utilize the information to construct a more promising solution, and thereby provide a systematic and elaborate reasoning method to guide the search directions of POLBBO. The proposed POLBBO is verified on a set of 24 benchmark functions with diverse complexities, and is compared with the basic BBO, five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms. The experimental results and comparisons demonstrate that the polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly in terms of the quality of the final solutions and the convergence rate. •An enhanced BBO variant (POLBBO) is developed for solving global numerical optimization problems.•A polyphyletic migration operator is proposed to generate new features from more promising areas in the search space.•An OL strategy is employed to provide a systematic reasoning method to guide the search directions of POLBBO.•The polyphyletic migration operator and the OL strategy can work together well and enhance the performance of BBO significantly.•Five state-of-the-art BBO variants, five existing OL-based algorithms, and nine other evolutionary algorithms are employed to compare.
Author	Shi, Dongyuan Xiong, Guojiang Duan, Xianzhong
Author_xml	– sequence: 1 givenname: Guojiang surname: Xiong fullname: Xiong, Guojiang – sequence: 2 givenname: Dongyuan surname: Shi fullname: Shi, Dongyuan email: dongyuanshi@hust.edu.cn – sequence: 3 givenname: Xianzhong surname: Duan fullname: Duan, Xianzhong
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Cites_doi	10.1016/j.cor.2012.10.014 10.1109/4235.752920 10.1016/j.cor.2012.04.012 10.1162/evco.1993.1.1.1 10.1016/j.ins.2011.04.024 10.1016/j.cor.2011.06.007 10.1016/j.apenergy.2013.04.095 10.1109/TEVC.2005.857610 10.1109/TSMCB.2011.2171946 10.1109/TEVC.2008.927706 10.1109/TSMCB.2012.2222373 10.1007/s10898-007-9149-x 10.1016/j.cor.2008.08.015 10.1016/j.cor.2010.11.004 10.1109/TEVC.2007.894200 10.1109/TPWRS.2009.2034525 10.1007/s10898-004-9972-2 10.1109/TEVC.2007.895272 10.1016/j.cor.2007.12.001 10.1109/TSMCB.2010.2056367 10.1007/s00500-010-0591-1 10.1016/j.eswa.2011.05.011 10.1109/TEVC.2008.919004 10.1016/j.cor.2011.03.003 10.1109/ICSMC.2009.5346043 10.1016/j.engappai.2010.08.005 10.1016/j.ejor.2006.06.043 10.1109/4235.910464 10.1109/4235.771163 10.1016/j.camwa.2012.04.015 10.1016/j.cor.2012.11.008 10.1023/A:1008202821328 10.1016/j.ins.2010.05.035 10.1109/TSMCA.2007.914796 10.1109/CCDC.2012.6244262 10.1016/j.amc.2008.08.053 10.1016/j.cor.2010.06.007 10.1016/j.amc.2010.03.123 10.1016/j.eswa.2009.11.033 10.1016/j.ins.2010.12.006 10.1109/ICNN.1995.488968 10.1016/j.amc.2011.05.110 10.1016/j.asoc.2011.12.020 10.1162/106365601750190398 10.1109/TEVC.2010.2052054 10.1016/j.asoc.2010.04.008 10.1109/TSMCB.2012.2213808 10.1016/j.ins.2011.09.001 10.1016/j.cor.2012.12.006 10.1016/j.eswa.2010.05.064 10.1109/TAP.2010.2055778
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Keywords	Global numerical optimization Orthogonal learning Biogeography-based optimization Orthogonal experimental design (OED) Polyphyletic migration operator Orthogonal design Probabilistic approach Useful information Evolutionary algorithm Migration Biogeography Global optimum Information retrieval Experimental result Experimental design Reasoning Heuristic method Convergence rate Defect Swarm intelligence Learning algorithm Numerical convergence
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References	Qin, Huang, Suganthan (bib52) 2009; 13 Ergezer M, Simon D, Du D. Oppositional biogeography-based optimization. In: Proceedings of the 2009 IEEE international conference on systems, man and cybernetics, Piscataway, NJ, USA; 2009. p. 1009–14. Sayed MM, Saad MS, Emara HM, Abou El-Zahab EE. A novel method for PID tuning using a modified biogeography-based optimization algorithm. In: Twenty-fourth Chinese control and decision conference (CCDC), Taiyuan; 2012. p. 1642–47. Gong, Cai, Ling (bib25) 2010; 15 Yao, Liu, Lin (bib43) 1999; 3 Noman, Iba (bib50) 2008; 12 Wang, Rahnamayan, Sun, Omran (bib55) 2013; 43 Goldberg (bib3) 1989 Gao, Liu (bib14) 2012; 39 Gong, Cai, Jiang (bib38) 2008; 206 Dorigo M, Di Caro G. Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation, Washington, DC; 1999. p. 1472–77. Zhang, Leung (bib36) 1999; 3 Gong, Cai, Ling, Li (bib30) 2010; 216 Kennedy J, Eberhart RC. Partical swarm optimization. In: Proceedings of the IEEE international conference on neural networks, Perth, WA; 1995. p. 1942–48. Xiong, Shi, Duan (bib24) 2013; 111 Jamuna, Swarup (bib23) 2012; 12 Boussaïd, Chatterjee, Siarry, Ahmed-Nacer (bib32) 2011; 38 Leung, Wang (bib37) 2001; 5 Wang, Cai, Zhang (bib41) 2012; 185 Hansen, Ostermeier (bib48) 2001; 9 Li, Yin (bib27) 2012; 64 Pan, Suganthan, Wang, Gao, Mallipeddi (bib7) 2011; 38 Li, Wang, Zhou, Yin (bib26) 2011; 218 Ho, Lin, Liauh, Ho (bib39) 2008; 38 Roy, Ghoshal, Thakur (bib22) 2010; 37 Bäck, Schwefel (bib1) 1993; 1 Schlüter, Egea, Banga (bib12) 2009; 36 Elsayed, Sarker, Essam (bib5) 2011; 38 Zhan, Zhang, Li, Shi (bib35) 2011; 15 Boussaïd, Chatterjee, Siarry, Ahmed-Nacer (bib19) 2012; 39 Simon, Rarick, Ergezer, Du (bib18) 2011; 181 Rahnamayan, Tizhoosh, Salama (bib51) 2008; 12 Singh, Kumar, Kamal (bib20) 2010; 58 Storn, Price (bib6) 1997; 11 Simon (bib16) 2008; 12 Xiang, An (bib15) 2013; 40 Ali, Khompatraporn, Zabinsky (bib45) 2005; 31 Li, Yang, Nguyen (bib54) 2012; 42 Drezner, MisevičIus (bib4) 2013; 40 Liang, Qin, Suganthan, Baskar (bib47) 2006; 10 Gao, Liu, Huang (bib42) 2013; 43 García-Villoria, Pastor (bib9) 2009; 36 Gong, Cai, Ling, Li (bib46) 2011; 41 Eiben, Smith (bib2) 2008 Nezhad, Shandiz, Jahromi (bib10) 2013; 40 Chan, Kwong, Jiang, Aydin, Fogarty (bib40) 2010; 37 Karaboga, Basturk (bib13) 2007; 39 Ma (bib17) 2010; 180 Garcia-Martinez, Lozano, Herrera, Molina, Sánchez (bib49) 2008; 185 Kang, Li, Ma (bib44) 2011; 181 Cai, Gong, Ling, Zhang (bib53) 2011; 11 Bhattacharya, Chattopadhyay (bib21) 2010; 25 Yang, Liu, Zhang, Feng (bib33) 2012 Ma, Simon (bib28) 2011; 24 Wang, Xu (bib34) 2011; 38 Drezner (10.1016/j.cor.2013.07.021_bib4) 2013; 40 Pan (10.1016/j.cor.2013.07.021_bib7) 2011; 38 Goldberg (10.1016/j.cor.2013.07.021_bib3) 1989 Yang (10.1016/j.cor.2013.07.021_bib33) 2012 Xiong (10.1016/j.cor.2013.07.021_bib24) 2013; 111 Yao (10.1016/j.cor.2013.07.021_bib43) 1999; 3 Liang (10.1016/j.cor.2013.07.021_bib47) 2006; 10 Wang (10.1016/j.cor.2013.07.021_bib41) 2012; 185 Xiang (10.1016/j.cor.2013.07.021_bib15) 2013; 40 Wang (10.1016/j.cor.2013.07.021_bib34) 2011; 38 Jamuna (10.1016/j.cor.2013.07.021_bib23) 2012; 12 Noman (10.1016/j.cor.2013.07.021_bib50) 2008; 12 Li (10.1016/j.cor.2013.07.021_bib54) 2012; 42 Elsayed (10.1016/j.cor.2013.07.021_bib5) 2011; 38 Simon (10.1016/j.cor.2013.07.021_bib16) 2008; 12 Cai (10.1016/j.cor.2013.07.021_bib53) 2011; 11 Li (10.1016/j.cor.2013.07.021_bib27) 2012; 64 Zhang (10.1016/j.cor.2013.07.021_bib36) 1999; 3 Boussaïd (10.1016/j.cor.2013.07.021_bib19) 2012; 39 Gong (10.1016/j.cor.2013.07.021_bib38) 2008; 206 Garcia-Martinez (10.1016/j.cor.2013.07.021_bib49) 2008; 185 Bäck (10.1016/j.cor.2013.07.021_bib1) 1993; 1 10.1016/j.cor.2013.07.021_bib11 Bhattacharya (10.1016/j.cor.2013.07.021_bib21) 2010; 25 Simon (10.1016/j.cor.2013.07.021_bib18) 2011; 181 Gong (10.1016/j.cor.2013.07.021_bib25) 2010; 15 Rahnamayan (10.1016/j.cor.2013.07.021_bib51) 2008; 12 Nezhad (10.1016/j.cor.2013.07.021_bib10) 2013; 40 Li (10.1016/j.cor.2013.07.021_bib26) 2011; 218 Wang (10.1016/j.cor.2013.07.021_bib55) 2013; 43 Storn (10.1016/j.cor.2013.07.021_bib6) 1997; 11 Gao (10.1016/j.cor.2013.07.021_bib14) 2012; 39 10.1016/j.cor.2013.07.021_bib29 Gong (10.1016/j.cor.2013.07.021_bib46) 2011; 41 Chan (10.1016/j.cor.2013.07.021_bib40) 2010; 37 Singh (10.1016/j.cor.2013.07.021_bib20) 2010; 58 Schlüter (10.1016/j.cor.2013.07.021_bib12) 2009; 36 Gao (10.1016/j.cor.2013.07.021_bib42) 2013; 43 Boussaïd (10.1016/j.cor.2013.07.021_bib32) 2011; 38 Ali (10.1016/j.cor.2013.07.021_bib45) 2005; 31 Ma (10.1016/j.cor.2013.07.021_bib28) 2011; 24 Hansen (10.1016/j.cor.2013.07.021_bib48) 2001; 9 García-Villoria (10.1016/j.cor.2013.07.021_bib9) 2009; 36 Gong (10.1016/j.cor.2013.07.021_bib30) 2010; 216 Ho (10.1016/j.cor.2013.07.021_bib39) 2008; 38 10.1016/j.cor.2013.07.021_bib31 Zhan (10.1016/j.cor.2013.07.021_bib35) 2011; 15 Eiben (10.1016/j.cor.2013.07.021_bib2) 2008 Karaboga (10.1016/j.cor.2013.07.021_bib13) 2007; 39 10.1016/j.cor.2013.07.021_bib8 Leung (10.1016/j.cor.2013.07.021_bib37) 2001; 5 Ma (10.1016/j.cor.2013.07.021_bib17) 2010; 180 Roy (10.1016/j.cor.2013.07.021_bib22) 2010; 37 Qin (10.1016/j.cor.2013.07.021_bib52) 2009; 13 Kang (10.1016/j.cor.2013.07.021_bib44) 2011; 181
References_xml	– volume: 40 start-page: 1038 year: 2013 end-page: 1046 ident: bib4 article-title: Enhancing the performance of hybrid genetic algorithms by differential improvement publication-title: Computers & Operations Research – volume: 31 start-page: 635 year: 2005 end-page: 672 ident: bib45 article-title: A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems publication-title: Journal of Global Optimization – volume: 15 start-page: 832 year: 2011 end-page: 847 ident: bib35 article-title: Orthogonal learning particle swarm optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 185 start-page: 1088 year: 2008 end-page: 1113 ident: bib49 article-title: Global and local real-coded genetic algorithms based on parent-centric crossover operators publication-title: European Journal of Operational Research – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: bib6 article-title: Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces publication-title: Journal of Global Optimization – volume: 10 start-page: 281 year: 2006 end-page: 295 ident: bib47 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation – start-page: 1 year: 2012 end-page: 12 ident: bib33 article-title: Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm publication-title: Applied Intelligence – volume: 5 start-page: 41 year: 2001 end-page: 53 ident: bib37 article-title: An orthogonal genetic algorithm with quantization for global numerical optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 36 start-page: 951 year: 2009 end-page: 966 ident: bib9 article-title: Introducing dynamic diversity into a discrete particle swarm optimization publication-title: Computers & Operations Research – volume: 24 start-page: 517 year: 2011 end-page: 525 ident: bib28 article-title: Blended biogeography-based optimization for constrained optimization publication-title: Engineering Applications of Artificial Intelligence – volume: 38 start-page: 15103 year: 2011 end-page: 15109 ident: bib34 article-title: An effective hybrid biogeography-based optimization algorithm for parameter estimation of chaotic systems publication-title: Expert Systems with Applications – volume: 11 start-page: 1363 year: 2011 end-page: 1379 ident: bib53 article-title: A clustering-based differential evolution for global optimization publication-title: Applied Soft Computing – volume: 15 start-page: 645 year: 2010 end-page: 665 ident: bib25 article-title: DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization publication-title: Soft Computing – reference: Kennedy J, Eberhart RC. Partical swarm optimization. In: Proceedings of the IEEE international conference on neural networks, Perth, WA; 1995. p. 1942–48. – volume: 39 start-page: 687 year: 2012 end-page: 697 ident: bib14 article-title: A modified artificial bee colony algorithm publication-title: Computers & Operations Research – volume: 216 start-page: 2749 year: 2010 end-page: 2758 ident: bib30 article-title: A real-coded biogeography-based optimization with mutation publication-title: Applied Mathematics and Computation – volume: 185 start-page: 153 year: 2012 end-page: 177 ident: bib41 article-title: Enhancing the search ability of differential evolution through orthogonal crossover publication-title: Information Sciences – volume: 25 start-page: 1064 year: 2010 end-page: 1077 ident: bib21 article-title: Biogeography-based optimization for different economic load dispatch problems publication-title: IEEE Transactions on Power Systems – volume: 38 start-page: 394 year: 2011 end-page: 408 ident: bib7 article-title: A differential evolution algorithm with self-adapting strategy and control parameters publication-title: Computers & Operations Research – volume: 1 start-page: 1 year: 1993 end-page: 23 ident: bib1 article-title: An overview of evolutionary algorithms for parameter optimization publication-title: Evolutionary Computation – reference: Dorigo M, Di Caro G. Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation, Washington, DC; 1999. p. 1472–77. – volume: 43 start-page: 1011 year: 2013 end-page: 1024 ident: bib42 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Transactions on Cybernetics – volume: 13 start-page: 398 year: 2009 end-page: 417 ident: bib52 article-title: Differential evolution algorithm with strategy adaptation for global numerical optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 12 start-page: 1503 year: 2012 end-page: 1510 ident: bib23 article-title: Multi-objective biogeography based optimization for optimal PMU placement publication-title: Applied Soft Computing – volume: 38 start-page: 288 year: 2008 end-page: 298 ident: bib39 article-title: OPSO: orthogonal particle swarm optimization and its application to task assignment problems publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part A: Systems and Humans – volume: 38 start-page: 1188 year: 2011 end-page: 1198 ident: bib32 article-title: Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO) publication-title: Computers & Operations Research – volume: 218 start-page: 598 year: 2011 end-page: 609 ident: bib26 article-title: A perturb biogeography based optimization with mutation for global numerical optimization publication-title: Applied Mathematics and Computation – year: 2008 ident: bib2 article-title: Introduction to evolutionary computing publication-title: , – volume: 111 start-page: 801 year: 2013 end-page: 811 ident: bib24 article-title: Multi-strategy ensemble biogeography-based optimization for economic dispatch problems publication-title: Applied Energy – volume: 181 start-page: 3508 year: 2011 end-page: 3531 ident: bib44 article-title: Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions publication-title: Information Sciences – volume: 38 start-page: 1877 year: 2011 end-page: 1896 ident: bib5 article-title: Multi-operator based evolutionary algorithms for solving constrained optimization problems publication-title: Computers & Operations Research – year: 1989 ident: bib3 article-title: Genetic algorithms in search, optimization, and machine learning publication-title: , – volume: 37 start-page: 3853 year: 2010 end-page: 3862 ident: bib40 article-title: A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design publication-title: Expert Systems with Applications – volume: 12 start-page: 107 year: 2008 end-page: 125 ident: bib50 article-title: Accelerating differential evolution using an adaptive local search publication-title: IEEE Transactions on Evolutionary Computation – volume: 12 start-page: 702 year: 2008 end-page: 713 ident: bib16 article-title: Biogeography-based optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 3 start-page: 53 year: 1999 end-page: 62 ident: bib36 article-title: An orthogonal genetic algorithm for multimedia multicast routing publication-title: IEEE Transactions on Evolutionary Computation – volume: 39 start-page: 459 year: 2007 end-page: 471 ident: bib13 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: Journal of Global Optimization – volume: 37 start-page: 8221 year: 2010 end-page: 8228 ident: bib22 article-title: Biogeography based optimization for multi-constraint optimal power flow with emission and non-smooth cost function publication-title: Expert Systems with Applications – volume: 42 start-page: 627 year: 2012 end-page: 646 ident: bib54 article-title: A self-learning particle swarm optimizer for global optimization problems publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics – volume: 180 start-page: 3444 year: 2010 end-page: 3464 ident: bib17 article-title: An analysis of the equilibrium of migration models for biogeography-based optimization publication-title: Information Sciences – volume: 3 start-page: 82 year: 1999 end-page: 102 ident: bib43 article-title: Evolutionary programming made faster publication-title: IEEE Transactions on Evolutionary Computation – volume: 41 start-page: 397 year: 2011 end-page: 413 ident: bib46 article-title: Enhanced differential evolution with adaptive strategies for numerical optimization publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics – volume: 39 start-page: 3293 year: 2012 end-page: 3304 ident: bib19 article-title: Biogeography-based optimization for constrained optimization problems publication-title: Computers & Operations Research – volume: 181 start-page: 1224 year: 2011 end-page: 1248 ident: bib18 article-title: Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms publication-title: Information Sciences – volume: 206 start-page: 56 year: 2008 end-page: 69 ident: bib38 article-title: Enhancing the performance of differential evolution using orthogonal design method publication-title: Applied Mathematics and Computation – volume: 12 start-page: 64 year: 2008 end-page: 79 ident: bib51 article-title: Opposition-based differential evolution publication-title: IEEE Transactions on Evolutionary Computation – volume: 9 start-page: 159 year: 2001 end-page: 195 ident: bib48 article-title: Completely derandomized self-adaptation in evolution strategies publication-title: Evolutionary Computation – reference: Ergezer M, Simon D, Du D. Oppositional biogeography-based optimization. In: Proceedings of the 2009 IEEE international conference on systems, man and cybernetics, Piscataway, NJ, USA; 2009. p. 1009–14. – volume: 40 start-page: 963 year: 2013 end-page: 972 ident: bib10 article-title: A particle swarm-BFGS algorithm for nonlinear programming problems publication-title: Computers & Operations Research – volume: 36 start-page: 2217 year: 2009 end-page: 2229 ident: bib12 article-title: Extended ant colony optimization for non-convex mixed integer nonlinear programming publication-title: Computers & Operations Research – volume: 40 start-page: 1256 year: 2013 end-page: 1265 ident: bib15 article-title: An efficient and robust artificial bee colony algorithm for numerical optimization publication-title: Computers & Operations Research – volume: 58 start-page: 3375 year: 2010 end-page: 3379 ident: bib20 article-title: Design of Yagi–Uda antenna using biogeography based optimization publication-title: IEEE Transactions on Antennas and Propagation – volume: 43 start-page: 634 year: 2013 end-page: 647 ident: bib55 article-title: Gaussian bare-bones differential evolution publication-title: IEEE Transactions on Cybernetics – volume: 64 start-page: 2833 year: 2012 end-page: 2844 ident: bib27 article-title: Multi-operator based biogeography based optimization with mutation for global numerical optimization publication-title: Computers & Mathematics with Applications – reference: Sayed MM, Saad MS, Emara HM, Abou El-Zahab EE. A novel method for PID tuning using a modified biogeography-based optimization algorithm. In: Twenty-fourth Chinese control and decision conference (CCDC), Taiyuan; 2012. p. 1642–47. – volume: 40 start-page: 1038 issue: 4 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib4 article-title: Enhancing the performance of hybrid genetic algorithms by differential improvement publication-title: Computers & Operations Research doi: 10.1016/j.cor.2012.10.014 – volume: 3 start-page: 53 issue: 1 year: 1999 ident: 10.1016/j.cor.2013.07.021_bib36 article-title: An orthogonal genetic algorithm for multimedia multicast routing publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.752920 – volume: 39 start-page: 3293 issue: 12 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib19 article-title: Biogeography-based optimization for constrained optimization problems publication-title: Computers & Operations Research doi: 10.1016/j.cor.2012.04.012 – volume: 1 start-page: 1 issue: 1 year: 1993 ident: 10.1016/j.cor.2013.07.021_bib1 article-title: An overview of evolutionary algorithms for parameter optimization publication-title: Evolutionary Computation doi: 10.1162/evco.1993.1.1.1 – volume: 181 start-page: 3508 issue: 16 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib44 article-title: Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions publication-title: Information Sciences doi: 10.1016/j.ins.2011.04.024 – volume: 39 start-page: 687 issue: 3 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib14 article-title: A modified artificial bee colony algorithm publication-title: Computers & Operations Research doi: 10.1016/j.cor.2011.06.007 – volume: 111 start-page: 801 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib24 article-title: Multi-strategy ensemble biogeography-based optimization for economic dispatch problems publication-title: Applied Energy doi: 10.1016/j.apenergy.2013.04.095 – volume: 10 start-page: 281 issue: 3 year: 2006 ident: 10.1016/j.cor.2013.07.021_bib47 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2005.857610 – volume: 42 start-page: 627 issue: 3 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib54 article-title: A self-learning particle swarm optimizer for global optimization problems publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics doi: 10.1109/TSMCB.2011.2171946 – volume: 13 start-page: 398 issue: 2 year: 2009 ident: 10.1016/j.cor.2013.07.021_bib52 article-title: Differential evolution algorithm with strategy adaptation for global numerical optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2008.927706 – volume: 43 start-page: 1011 issue: 3 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib42 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TSMCB.2012.2222373 – volume: 39 start-page: 459 issue: 3 year: 2007 ident: 10.1016/j.cor.2013.07.021_bib13 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: Journal of Global Optimization doi: 10.1007/s10898-007-9149-x – volume: 36 start-page: 2217 issue: 7 year: 2009 ident: 10.1016/j.cor.2013.07.021_bib12 article-title: Extended ant colony optimization for non-convex mixed integer nonlinear programming publication-title: Computers & Operations Research doi: 10.1016/j.cor.2008.08.015 – volume: 38 start-page: 1188 issue: 8 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib32 article-title: Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO) publication-title: Computers & Operations Research doi: 10.1016/j.cor.2010.11.004 – volume: 12 start-page: 64 issue: 1 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib51 article-title: Opposition-based differential evolution publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2007.894200 – volume: 25 start-page: 1064 issue: 2 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib21 article-title: Biogeography-based optimization for different economic load dispatch problems publication-title: IEEE Transactions on Power Systems doi: 10.1109/TPWRS.2009.2034525 – volume: 31 start-page: 635 issue: 4 year: 2005 ident: 10.1016/j.cor.2013.07.021_bib45 article-title: A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems publication-title: Journal of Global Optimization doi: 10.1007/s10898-004-9972-2 – volume: 12 start-page: 107 issue: 1 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib50 article-title: Accelerating differential evolution using an adaptive local search publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2007.895272 – volume: 36 start-page: 951 issue: 3 year: 2009 ident: 10.1016/j.cor.2013.07.021_bib9 article-title: Introducing dynamic diversity into a discrete particle swarm optimization publication-title: Computers & Operations Research doi: 10.1016/j.cor.2007.12.001 – volume: 41 start-page: 397 issue: 2 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib46 article-title: Enhanced differential evolution with adaptive strategies for numerical optimization publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics doi: 10.1109/TSMCB.2010.2056367 – volume: 15 start-page: 645 issue: 4 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib25 article-title: DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization publication-title: Soft Computing doi: 10.1007/s00500-010-0591-1 – volume: 38 start-page: 15103 issue: 12 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib34 article-title: An effective hybrid biogeography-based optimization algorithm for parameter estimation of chaotic systems publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2011.05.011 – volume: 12 start-page: 702 issue: 6 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib16 article-title: Biogeography-based optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2008.919004 – volume: 38 start-page: 1877 issue: 12 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib5 article-title: Multi-operator based evolutionary algorithms for solving constrained optimization problems publication-title: Computers & Operations Research doi: 10.1016/j.cor.2011.03.003 – ident: 10.1016/j.cor.2013.07.021_bib31 doi: 10.1109/ICSMC.2009.5346043 – volume: 24 start-page: 517 issue: 3 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib28 article-title: Blended biogeography-based optimization for constrained optimization publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2010.08.005 – volume: 185 start-page: 1088 issue: 3 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib49 article-title: Global and local real-coded genetic algorithms based on parent-centric crossover operators publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2006.06.043 – volume: 5 start-page: 41 issue: 1 year: 2001 ident: 10.1016/j.cor.2013.07.021_bib37 article-title: An orthogonal genetic algorithm with quantization for global numerical optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.910464 – volume: 3 start-page: 82 issue: 2 year: 1999 ident: 10.1016/j.cor.2013.07.021_bib43 article-title: Evolutionary programming made faster publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.771163 – volume: 64 start-page: 2833 issue: 9 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib27 article-title: Multi-operator based biogeography based optimization with mutation for global numerical optimization publication-title: Computers & Mathematics with Applications doi: 10.1016/j.camwa.2012.04.015 – volume: 40 start-page: 963 issue: 4 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib10 article-title: A particle swarm-BFGS algorithm for nonlinear programming problems publication-title: Computers & Operations Research doi: 10.1016/j.cor.2012.11.008 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 10.1016/j.cor.2013.07.021_bib6 article-title: Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces publication-title: Journal of Global Optimization doi: 10.1023/A:1008202821328 – ident: 10.1016/j.cor.2013.07.021_bib11 – volume: 180 start-page: 3444 issue: 18 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib17 article-title: An analysis of the equilibrium of migration models for biogeography-based optimization publication-title: Information Sciences doi: 10.1016/j.ins.2010.05.035 – volume: 38 start-page: 288 issue: 2 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib39 article-title: OPSO: orthogonal particle swarm optimization and its application to task assignment problems publication-title: IEEE Transactions on Systems, Man, and Cybernetics. Part A: Systems and Humans doi: 10.1109/TSMCA.2007.914796 – ident: 10.1016/j.cor.2013.07.021_bib29 doi: 10.1109/CCDC.2012.6244262 – volume: 206 start-page: 56 issue: 1 year: 2008 ident: 10.1016/j.cor.2013.07.021_bib38 article-title: Enhancing the performance of differential evolution using orthogonal design method publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2008.08.053 – year: 2008 ident: 10.1016/j.cor.2013.07.021_bib2 article-title: Introduction to evolutionary computing – volume: 38 start-page: 394 issue: 1 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib7 article-title: A differential evolution algorithm with self-adapting strategy and control parameters publication-title: Computers & Operations Research doi: 10.1016/j.cor.2010.06.007 – volume: 216 start-page: 2749 issue: 9 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib30 article-title: A real-coded biogeography-based optimization with mutation publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2010.03.123 – volume: 37 start-page: 3853 issue: 5 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib40 article-title: A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2009.11.033 – volume: 181 start-page: 1224 issue: 7 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib18 article-title: Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms publication-title: Information Sciences doi: 10.1016/j.ins.2010.12.006 – start-page: 1 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib33 article-title: Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm publication-title: Applied Intelligence – ident: 10.1016/j.cor.2013.07.021_bib8 doi: 10.1109/ICNN.1995.488968 – volume: 218 start-page: 598 issue: 2 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib26 article-title: A perturb biogeography based optimization with mutation for global numerical optimization publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2011.05.110 – volume: 12 start-page: 1503 issue: 5 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib23 article-title: Multi-objective biogeography based optimization for optimal PMU placement publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2011.12.020 – volume: 9 start-page: 159 issue: 2 year: 2001 ident: 10.1016/j.cor.2013.07.021_bib48 article-title: Completely derandomized self-adaptation in evolution strategies publication-title: Evolutionary Computation doi: 10.1162/106365601750190398 – volume: 15 start-page: 832 issue: 6 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib35 article-title: Orthogonal learning particle swarm optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2010.2052054 – volume: 11 start-page: 1363 issue: 1 year: 2011 ident: 10.1016/j.cor.2013.07.021_bib53 article-title: A clustering-based differential evolution for global optimization publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2010.04.008 – volume: 43 start-page: 634 issue: 2 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib55 article-title: Gaussian bare-bones differential evolution publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TSMCB.2012.2213808 – volume: 185 start-page: 153 issue: 1 year: 2012 ident: 10.1016/j.cor.2013.07.021_bib41 article-title: Enhancing the search ability of differential evolution through orthogonal crossover publication-title: Information Sciences doi: 10.1016/j.ins.2011.09.001 – volume: 40 start-page: 1256 issue: 5 year: 2013 ident: 10.1016/j.cor.2013.07.021_bib15 article-title: An efficient and robust artificial bee colony algorithm for numerical optimization publication-title: Computers & Operations Research doi: 10.1016/j.cor.2012.12.006 – year: 1989 ident: 10.1016/j.cor.2013.07.021_bib3 article-title: Genetic algorithms in search, optimization, and machine learning – volume: 37 start-page: 8221 issue: 12 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib22 article-title: Biogeography based optimization for multi-constraint optimal power flow with emission and non-smooth cost function publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2010.05.064 – volume: 58 start-page: 3375 issue: 10 year: 2010 ident: 10.1016/j.cor.2013.07.021_bib20 article-title: Design of Yagi–Uda antenna using biogeography based optimization publication-title: IEEE Transactions on Antennas and Propagation doi: 10.1109/TAP.2010.2055778
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Snippet	Biogeography-based optimization (BBO) is a powerful population-based algorithm inspired by biogeography and has been extensively applied to many science and...
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SubjectTerms	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Biogeography Biogeography-based optimization Computer science; control theory; systems Design of experiments Exact sciences and technology Experimental design Global numerical optimization Mathematical analysis Mathematical models Mathematical problems Mathematics Migration Operations research Operators Optimization algorithms Orthogonal experimental design (OED) Orthogonal learning Performance enhancement Polyphyletic migration operator Probability and statistics Sciences and techniques of general use Searching Statistics Strategy Studies Theoretical computing Vector space
Title	Enhancing the performance of biogeography-based optimization using polyphyletic migration operator and orthogonal learning
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