Loser-Out Tournament-Based Fireworks Algorithm for Multimodal Function Optimization
Real-world optimization problems are usually multimodal which require optimization algorithms to keep a balance between exploration and exploitation. Therefore, multimodal optimization is one of the main opportunities as well as one of the main challenges for evolutionary algorithms. In this paper,...
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| Published in: | IEEE transactions on evolutionary computation Vol. 22; no. 5; pp. 679 - 691 |
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| Language: | English |
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IEEE
01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1089-778X, 1941-0026 |
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| Abstract | Real-world optimization problems are usually multimodal which require optimization algorithms to keep a balance between exploration and exploitation. Therefore, multimodal optimization is one of the main opportunities as well as one of the main challenges for evolutionary algorithms. In this paper, a loser-out tournament-based fireworks algorithm (LoTFWA) is proposed for solving multimodal optimization problems. The search manner of the conventional fireworks algorithm (FWA) is based on the cooperation of several fireworks. While in the LoTFWA, we propose competition as a new manner of interaction, in which the fireworks are compared with each other not only according to their current status but also according to their progress rate. If the fitness of a certain firework cannot catch up with the best one with its current progress rate, it is considered a loser in the competition. The losers will be eliminated and reinitialized because it is vain to continue their search processes. Reinitializing these fireworks would greatly reduce the probability of being trapped in local minima for the algorithm. Experimental results show that the proposed algorithm is very powerful in optimizing multimodal functions. It not only outperforms previous versions of the FWA, but also outperforms several famous evolutionary algorithms. |
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| AbstractList | Real-world optimization problems are usually multimodal which require optimization algorithms to keep a balance between exploration and exploitation. Therefore, multimodal optimization is one of the main opportunities as well as one of the main challenges for evolutionary algorithms. In this paper, a loser-out tournament-based fireworks algorithm (LoTFWA) is proposed for solving multimodal optimization problems. The search manner of the conventional fireworks algorithm (FWA) is based on the cooperation of several fireworks. While in the LoTFWA, we propose competition as a new manner of interaction, in which the fireworks are compared with each other not only according to their current status but also according to their progress rate. If the fitness of a certain firework cannot catch up with the best one with its current progress rate, it is considered a loser in the competition. The losers will be eliminated and reinitialized because it is vain to continue their search processes. Reinitializing these fireworks would greatly reduce the probability of being trapped in local minima for the algorithm. Experimental results show that the proposed algorithm is very powerful in optimizing multimodal functions. It not only outperforms previous versions of the FWA, but also outperforms several famous evolutionary algorithms. |
| Author | Tan, Ying Li, Junzhi |
| Author_xml | – sequence: 1 givenname: Junzhi orcidid: 0000-0002-5476-823X surname: Li fullname: Li, Junzhi email: ljz@pku.edu.cn organization: Department of Machine Intelligence, Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China – sequence: 2 givenname: Ying orcidid: 0000-0001-8243-4731 surname: Tan fullname: Tan, Ying email: ytan@pku.edu.cn organization: Department of Machine Intelligence, Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China |
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| Cites_doi | 10.1109/TCBB.2015.2497227 10.1109/TEVC.2008.920671 10.1093/oso/9780195099713.001.0001 10.4018/ijsir.2013100103 10.4018/IJSIR.2015070101 10.1007/BF00175354 10.1023/A:1022602019183 10.1017/CBO9780511804441 10.1007/978-3-540-92910-9_32 10.1109/TCBB.2015.2446487 10.1023/A:1008202821328 10.1007/978-3-319-11857-4_55 10.1007/978-3-662-46353-6_9 10.1007/11553090_88 10.1109/4235.585892 10.1109/CEC.2014.6900590 10.1016/j.asoc.2017.10.046 10.1109/TCYB.2015.2474153 10.1016/j.neucom.2012.08.075 10.1109/TEVC.2016.2589821 10.1109/SIS.2013.6615186 10.1109/CEC.2014.6900418 10.1109/CEC.2013.6557799 10.1109/CEC.2013.6557848 10.1109/CEC.2013.6557583 10.1007/978-1-4615-1539-5_3 10.7208/chicago/9780226797670.001.0001 10.1109/72.508930 10.1109/CEC.2013.6557593 10.1109/TEVC.2014.2308294 10.4018/IJSIR.2015070103 10.1007/978-3-642-13495-1_44 10.1007/978-3-642-38703-6_2 10.1109/ICEC.1994.350042 10.1201/9781420036206 10.1109/CEC.2013.6557832 10.1109/CEC.2014.6900485 10.1109/CEC.2015.7257031 10.1145/2480741.2480752 10.1109/CEC.2005.1554902 10.1162/evco.1993.1.2.101 10.1007/BF00047572 10.1109/CEC.2015.7257030 |
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| References | rechenberg (ref6) 1994; 1 ref59 ref14 ref52 ref55 ref11 ref10 horn (ref44) 1997 ref16 ref19 ref18 liang (ref57) 2013 tan (ref1) 2010 ref51 (ref36) 2017 moscato (ref13) 1989 ref46 ref45 pedersen (ref56) 2010 ref48 ref42 ref41 ref43 clerc (ref58) 2011 ref49 mahfoud (ref50) 1995 (ref37) 2017 ref9 ref4 ref3 hwang (ref8) 1988; 12 ref5 ref40 ref35 ref34 reynolds (ref12) 1994 ref33 ref32 zaharie (ref20) 2004 ref2 ref38 (ref54) 2017 kennedy (ref7) 2011 goh (ref47) 2009; 13 ref24 ref26 ref25 ref21 bäck (ref15) 1996 ref28 li (ref39) 2018; 62 ref27 ref29 lourenço (ref17) 2010 sheng (ref53) 2016; 20 suganthan (ref63) 2017 ref60 branke (ref23) 2000 ref62 ref61 liu (ref30) 2014 zheng (ref31) 2013 blackwell (ref22) 2004 |
| References_xml | – ident: ref2 doi: 10.1109/TCBB.2015.2497227 – volume: 13 start-page: 103 year: 2009 ident: ref47 article-title: A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2008.920671 – year: 1996 ident: ref15 publication-title: Evolutionary Algorithms in Theory and Practice Evolution Strategies Evolutionary Programming Genetic Algorithms doi: 10.1093/oso/9780195099713.001.0001 – ident: ref35 doi: 10.4018/ijsir.2013100103 – ident: ref28 doi: 10.4018/IJSIR.2015070101 – start-page: 17 year: 2004 ident: ref20 article-title: A multipopulation differential evolution algorithm for multimodal optimization publication-title: Proc MENDEL – ident: ref9 doi: 10.1007/BF00175354 – ident: ref45 doi: 10.1023/A:1022602019183 – ident: ref5 doi: 10.1017/CBO9780511804441 – ident: ref19 doi: 10.1007/978-3-540-92910-9_32 – ident: ref4 doi: 10.1109/TCBB.2015.2446487 – year: 2017 ident: ref36 publication-title: Power Law Distribution – year: 1997 ident: ref44 article-title: The nature of niching: Genetic algorithms and the evolution of optimal, cooperative populations – ident: ref10 doi: 10.1023/A:1008202821328 – ident: ref25 doi: 10.1007/978-3-319-11857-4_55 – year: 2013 ident: ref57 article-title: Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization – ident: ref3 doi: 10.1007/978-3-662-46353-6_9 – ident: ref21 doi: 10.1007/11553090_88 – ident: ref11 doi: 10.1109/4235.585892 – ident: ref41 doi: 10.1109/CEC.2014.6900590 – volume: 62 start-page: 454 year: 2018 ident: ref39 article-title: The bare bones fireworks algorithm: A minimalist global optimizer publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2017.10.046 – year: 2011 ident: ref58 article-title: Standard particle swarm optimization, from 2006 to 2011 publication-title: Particle Swarm Central – ident: ref49 doi: 10.1109/TCYB.2015.2474153 – ident: ref40 doi: 10.1016/j.neucom.2012.08.075 – ident: ref38 doi: 10.1109/TEVC.2016.2589821 – ident: ref52 doi: 10.1109/SIS.2013.6615186 – volume: 1 year: 1994 ident: ref6 article-title: Evolution strategy publication-title: Computational Intelligence Imitating Life – start-page: 2069 year: 2013 ident: ref31 article-title: Enhanced fireworks algorithm publication-title: Proc IEEE Congr Evol Comput (CEC) – start-page: 489 year: 2004 ident: ref22 publication-title: Multi-swarm optimization in dynamic environments – year: 2017 ident: ref63 publication-title: Results of 22 Papers – start-page: 1989 year: 1989 ident: ref13 article-title: On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms – ident: ref33 doi: 10.1109/CEC.2014.6900418 – ident: ref62 doi: 10.1109/CEC.2013.6557799 – ident: ref59 doi: 10.1109/CEC.2013.6557848 – volume: 20 start-page: 838 year: 2016 ident: ref53 article-title: Adaptive multisubpopulation competition and multiniche crowding-based memetic algorithm for automatic data clustering publication-title: IEEE Trans Evol Comput – ident: ref51 doi: 10.1109/CEC.2013.6557583 – ident: ref42 doi: 10.1007/978-1-4615-1539-5_3 – ident: ref48 doi: 10.7208/chicago/9780226797670.001.0001 – year: 2010 ident: ref56 article-title: Tuning & simplifying heuristical optimization – ident: ref46 doi: 10.1109/72.508930 – ident: ref61 doi: 10.1109/CEC.2013.6557593 – start-page: 131 year: 1994 ident: ref12 article-title: An introduction to cultural algorithms publication-title: Proc 3rd Annu Conf Evol Program – year: 2017 ident: ref54 publication-title: Single Combat – start-page: 62 year: 1995 ident: ref50 article-title: Niching methods for genetic algorithms – ident: ref16 doi: 10.1109/TEVC.2014.2308294 – start-page: 3207 year: 2014 ident: ref30 article-title: Analysis on global convergence and time complexity of fireworks algorithm publication-title: Proc IEEE Congr Evol Comput (CEC) – ident: ref29 doi: 10.4018/IJSIR.2015070103 – start-page: 363 year: 2010 ident: ref17 publication-title: ch Iterated Local Search Framework and Applications – start-page: 299 year: 2000 ident: ref23 publication-title: A Multi-Population Approach to Dynamic Optimization Problems – year: 2017 ident: ref37 publication-title: 80/20 Rule – start-page: 355 year: 2010 ident: ref1 article-title: Fireworks algorithm for optimization publication-title: Advances in Swarm Intelligence doi: 10.1007/978-3-642-13495-1_44 – ident: ref32 doi: 10.1007/978-3-642-38703-6_2 – ident: ref14 doi: 10.1109/ICEC.1994.350042 – ident: ref55 doi: 10.1201/9781420036206 – ident: ref60 doi: 10.1109/CEC.2013.6557832 – ident: ref34 doi: 10.1109/CEC.2014.6900485 – start-page: 760 year: 2011 ident: ref7 article-title: Particle swarm optimization publication-title: Encyclopedia of Machine Learning – ident: ref27 doi: 10.1109/CEC.2015.7257031 – ident: ref43 doi: 10.1145/2480741.2480752 – ident: ref18 doi: 10.1109/CEC.2005.1554902 – ident: ref24 doi: 10.1162/evco.1993.1.2.101 – volume: 12 start-page: 108 year: 1988 ident: ref8 article-title: Simulated annealing: Theory and applications publication-title: Acta Applicandae Mathematicae doi: 10.1007/BF00047572 – ident: ref26 doi: 10.1109/CEC.2015.7257030 |
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| SubjectTerms | Competition Evolutionary algorithm Evolutionary algorithms Evolutionary computation Explosions Fireworks fireworks algorithm (FWA) Fitness Genetic algorithms Heuristic algorithms loser-out tournament (LoT) multimodal optimization Optimization Optimization algorithms Sociology Sparks Statistics swarm intelligence |
| Title | Loser-Out Tournament-Based Fireworks Algorithm for Multimodal Function Optimization |
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