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Erschienen in: Soft Computing 20/2017

29.08.2016 | Focus

New mutation strategies of differential evolution based on clearing niche mechanism

verfasst von: Yanan Li, Haixiang Guo, Xiao Liu, Yijing Li, Wenwen Pan, Bing Gong, Shaoning Pang

Erschienen in: Soft Computing | Ausgabe 20/2017

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Abstract

Although differential evolution (DE) algorithms have been widely proposed for tackling various of problems, the trade-off among population diversity, global and local exploration ability, and convergence rate is hard to maintain with the existing strategies. From this respective, this paper presents some new mutation strategies of DE by applying the clearing niche mechanism to the existing mutation strategies. Insteading of using random, best or target individuals as base vector, the niche individuals are utilized in these strategies. As the base vector is from a subpopulation, which is made up of the best individuals in each niche, the base vector can be guided by the global or local best ones. This mechanism is beneficial to the balance among population diversity, search capability, and convergence rate of DE, since it can both enhance the population diversity and search capability. Extensive experimental results indicate that the proposed strategies based on clearing niche mechanism can effectively enhance DE’s performance.

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Literatur
Zurück zum Zitat Al-Dabbagh RD, Kinsheel A, Mekhilef S et al (2014) System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm. Adv Eng Softw 78:60–66CrossRef Al-Dabbagh RD, Kinsheel A, Mekhilef S et al (2014) System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm. Adv Eng Softw 78:60–66CrossRef
Zurück zum Zitat Ali M, Ahn CW, Siarry P (2014) Differential evolution algorithm for the selection of optimal scaling factors in image watermarking. Eng Appl Artif Intell 31:15–26CrossRef Ali M, Ahn CW, Siarry P (2014) Differential evolution algorithm for the selection of optimal scaling factors in image watermarking. Eng Appl Artif Intell 31:15–26CrossRef
Zurück zum Zitat Basu M (2011) Economic environmental dispatch using multi-objective differential evolution. Appl Soft Comput 11(2):2845–2853CrossRef Basu M (2011) Economic environmental dispatch using multi-objective differential evolution. Appl Soft Comput 11(2):2845–2853CrossRef
Zurück zum Zitat Biswas S, Kundu S, Das S (2014) An improved parent-centric mutation with normalized neighborhoods for inducing niching behavior in differential evolution. IEEE Trans Cybern 44(10):1726–1737CrossRef Biswas S, Kundu S, Das S (2014) An improved parent-centric mutation with normalized neighborhoods for inducing niching behavior in differential evolution. IEEE Trans Cybern 44(10):1726–1737CrossRef
Zurück zum Zitat Brest J, Mernik M (2008) Population size reduction for the differential evolution algorithm. Appl Intell 29(3):228–247CrossRef Brest J, Mernik M (2008) Population size reduction for the differential evolution algorithm. Appl Intell 29(3):228–247CrossRef
Zurück zum Zitat Das R, Prasad DK (2015) Prediction of porosity and thermal diffusivity in a porous fin using differential evolution algorithm. Swarm Evol Comput 23:27–39CrossRef Das R, Prasad DK (2015) Prediction of porosity and thermal diffusivity in a porous fin using differential evolution algorithm. Swarm Evol Comput 23:27–39CrossRef
Zurück zum Zitat Epitropakis MG, Li X, Burke EK (2013) A dynamic archive niching differential evolution algorithm for multimodal optimization. In: IEEE Congress on Evolutionary Computation (CEC 2013), pp 79–86 Epitropakis MG, Li X, Burke EK (2013) A dynamic archive niching differential evolution algorithm for multimodal optimization. In: IEEE Congress on Evolutionary Computation (CEC 2013), pp 79–86
Zurück zum Zitat Epitropakis MG, Plagianakos VP, Vrahat MN (2012) Multimodal optimization using niching differential evolution with index-based neighborhoods. In: IEEE Congress on Evolutionary Computation (CEC 2012), pp 1–8 Epitropakis MG, Plagianakos VP, Vrahat MN (2012) Multimodal optimization using niching differential evolution with index-based neighborhoods. In: IEEE Congress on Evolutionary Computation (CEC 2012), pp 1–8
Zurück zum Zitat Han MF, Lin CT, Chang JY (2013) Differential evolution with local information for neuro-fuzzy systems optimization. Knowl Based Syst 44:78–89CrossRef Han MF, Lin CT, Chang JY (2013) Differential evolution with local information for neuro-fuzzy systems optimization. Knowl Based Syst 44:78–89CrossRef
Zurück zum Zitat Ho-Huu V, Nguyen-Thoi T, Nguyen-Thoi MH et al (2015) An improved constrained differential evolution using discrete variables (D-ICDE) for layout optimization of truss structures. Expert Syst Appl 42(20):7057–7069CrossRef Ho-Huu V, Nguyen-Thoi T, Nguyen-Thoi MH et al (2015) An improved constrained differential evolution using discrete variables (D-ICDE) for layout optimization of truss structures. Expert Syst Appl 42(20):7057–7069CrossRef
Zurück zum Zitat Kundu S, Das S, Vasilakos AV et al (2014) A modified differential evolution-based combined routing and sleep scheduling scheme for lifetime maximization of wireless sensor networks. Soft Comput 19(3):637–659CrossRef Kundu S, Das S, Vasilakos AV et al (2014) A modified differential evolution-based combined routing and sleep scheduling scheme for lifetime maximization of wireless sensor networks. Soft Comput 19(3):637–659CrossRef
Zurück zum Zitat Li X (2005) Efficient differential evolution using speciation for multimodal function optimization. In: The 7th annual conference on genetic and evolutionary computation, ACM, pp 873–880 Li X (2005) Efficient differential evolution using speciation for multimodal function optimization. In: The 7th annual conference on genetic and evolutionary computation, ACM, pp 873–880
Zurück zum Zitat Liang JJ, Suganthan PN, Deb K (2005) Novel composition test functions for numerical global optimization. In: Swarm Intelligence Symposium, pp 68–75 Liang JJ, Suganthan PN, Deb K (2005) Novel composition test functions for numerical global optimization. In: Swarm Intelligence Symposium, pp 68–75
Zurück zum Zitat Liu JH, Lampinen J (2002) On setting the control parameter of the differential evolution method. In: The 8th international conference on soft computing (MENDEL 2002), pp 11–18 Liu JH, Lampinen J (2002) On setting the control parameter of the differential evolution method. In: The 8th international conference on soft computing (MENDEL 2002), pp 11–18
Zurück zum Zitat Liu G, Xiong C, Guo Z (2014) Enhanced differential evolution using random-based sampling and neighborhood mutation. Soft Comput 19(8):1–20 Liu G, Xiong C, Guo Z (2014) Enhanced differential evolution using random-based sampling and neighborhood mutation. Soft Comput 19(8):1–20
Zurück zum Zitat Mahfoud SW (1995) Niching methods for genetic algorithms, Ph.D. dissertation, Univ. of Illinois, Urbana-Champaign Mahfoud SW (1995) Niching methods for genetic algorithms, Ph.D. dissertation, Univ. of Illinois, Urbana-Champaign
Zurück zum Zitat Mallipeddi R, Suganthan PN, Pan QK et al (2011) Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl Soft Comput 11(2):1679–1696CrossRef Mallipeddi R, Suganthan PN, Pan QK et al (2011) Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl Soft Comput 11(2):1679–1696CrossRef
Zurück zum Zitat Mallipeddi R, Lee M (2015) An evolving surrogate model-based differential evolution algorithm. Appl Soft Comput 34:770–787CrossRef Mallipeddi R, Lee M (2015) An evolving surrogate model-based differential evolution algorithm. Appl Soft Comput 34:770–787CrossRef
Zurück zum Zitat Mohamed AW (2015) An improved differential evolution algorithm with triangular mutation for global numerical optimization. Comput Ind Eng 85:359–375CrossRef Mohamed AW (2015) An improved differential evolution algorithm with triangular mutation for global numerical optimization. Comput Ind Eng 85:359–375CrossRef
Zurück zum Zitat Mokhtari H, Salmasnia A (2015) A monte carlo simulation based chaotic differential evolution algorithm for scheduling a stochastic parallel processor system. Expert Syst Appl 42(20):7132–7147CrossRef Mokhtari H, Salmasnia A (2015) A monte carlo simulation based chaotic differential evolution algorithm for scheduling a stochastic parallel processor system. Expert Syst Appl 42(20):7132–7147CrossRef
Zurück zum Zitat Petrowski A (1996) A clearing procedure as a niching method for genetic algorithms. In: The 1996 IEEE international conference on evolutionary computation, pp 798–803 Petrowski A (1996) A clearing procedure as a niching method for genetic algorithms. In: The 1996 IEEE international conference on evolutionary computation, pp 798–803
Zurück zum Zitat Petrowski A, Genet MG (1999) A classification tree for speciation. In: IEEE Congress on Evolutionary Computation (CEC 1999), vol 1, pp 204–211 Petrowski A, Genet MG (1999) A classification tree for speciation. In: IEEE Congress on Evolutionary Computation (CEC 1999), vol 1, pp 204–211
Zurück zum Zitat Qin AK, Suganthan PN (2005) Self-adaptive differential evolution algorithm for numerical optimization. In: IEEE congress on evolutionary computation (CEC 2005), vol 2, IEEE Press, pp 1785–1791 Qin AK, Suganthan PN (2005) Self-adaptive differential evolution algorithm for numerical optimization. In: IEEE congress on evolutionary computation (CEC 2005), vol 2, IEEE Press, pp 1785–1791
Zurück zum Zitat Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evolut Comput 13(2):398–417CrossRef Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evolut Comput 13(2):398–417CrossRef
Zurück zum Zitat Rakshit P, Konar A (2015) Differential evolution for noisy multi-objective optimization. Artif Intell 227:165–189CrossRefMATH Rakshit P, Konar A (2015) Differential evolution for noisy multi-objective optimization. Artif Intell 227:165–189CrossRefMATH
Zurück zum Zitat Sareni B, Krahenbuhl L (1998) Fitness sharing and niching methods revisited. IEEE Trans Evolut Comput 3(2):97–106CrossRef Sareni B, Krahenbuhl L (1998) Fitness sharing and niching methods revisited. IEEE Trans Evolut Comput 3(2):97–106CrossRef
Zurück zum Zitat Secmen M, Tasgetiren MF (2013) Ensemble of differential evolution algorithms for electromagnetic target recognition problem. IET Radar Sonar Navig 7(7):780–788CrossRef Secmen M, Tasgetiren MF (2013) Ensemble of differential evolution algorithms for electromagnetic target recognition problem. IET Radar Sonar Navig 7(7):780–788CrossRef
Zurück zum Zitat Sharma S, Rangaiah GP (2013) An improved multi-objective differential evolution with a termination criterion for optimizing chemical processes. Comput Chem Eng 56:155–173CrossRef Sharma S, Rangaiah GP (2013) An improved multi-objective differential evolution with a termination criterion for optimizing chemical processes. Comput Chem Eng 56:155–173CrossRef
Zurück zum Zitat Sheniha SF, Priyadharsini SS, Rajan SE (2013) Removal of artifact from EEG signal using differential evolution algorithm. In: The 2th international conference on communication and signal processing, pp 134–138 Sheniha SF, Priyadharsini SS, Rajan SE (2013) Removal of artifact from EEG signal using differential evolution algorithm. In: The 2th international conference on communication and signal processing, pp 134–138
Zurück zum Zitat Simionescu PA (2014) Computer-aided graphing and simulation tools for AutoCAD User, (1st Ed.) CRC Press, Boca Raton Simionescu PA (2014) Computer-aided graphing and simulation tools for AutoCAD User, (1st Ed.) CRC Press, Boca Raton
Zurück zum Zitat Storn R, Price KV (1996) Minimizing the real functions of the ICEC 1996 contest by differential evolution. In: Proceedings: 1996 IEEE international conference on evolutionary computation, pp 842–844 Storn R, Price KV (1996) Minimizing the real functions of the ICEC 1996 contest by differential evolution. In: Proceedings: 1996 IEEE international conference on evolutionary computation, pp 842–844
Zurück zum Zitat Tang L, Dong Y, Liu J (2015) Differential evolution with an individual-dependent mechanism. IEEE Trans Evolut Comput 19(4):560–574CrossRef Tang L, Dong Y, Liu J (2015) Differential evolution with an individual-dependent mechanism. IEEE Trans Evolut Comput 19(4):560–574CrossRef
Zurück zum Zitat Thomsen R (2004) Multimodal optimization using crowding-based differential evolution. In: IEEE Congress on Evolutionary Computation (CEC 2004) vol 2, pp 1382–1389 Thomsen R (2004) Multimodal optimization using crowding-based differential evolution. In: IEEE Congress on Evolutionary Computation (CEC 2004) vol 2, pp 1382–1389
Zurück zum Zitat Tvrdík J, Křivý I (2015) Hybrid differential evolution algorithm for optimal clustering. Appl Soft Comput 35:502–512CrossRef Tvrdík J, Křivý I (2015) Hybrid differential evolution algorithm for optimal clustering. Appl Soft Comput 35:502–512CrossRef
Zurück zum Zitat Walters DC, Sheble GB (1993) Genetic algorithm solution of economic dispatch with valve point loading. IEEE Trans Power Syst 8(3):1325–1332CrossRef Walters DC, Sheble GB (1993) Genetic algorithm solution of economic dispatch with valve point loading. IEEE Trans Power Syst 8(3):1325–1332CrossRef
Zurück zum Zitat Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evolut Comput 15(1):55–66CrossRef Wang Y, Cai Z, Zhang Q (2011) Differential evolution with composite trial vector generation strategies and control parameters. IEEE Trans Evolut Comput 15(1):55–66CrossRef
Zurück zum Zitat Wang J, Liao J, Zhou Y et al (2014) Differential evolution enhanced with multiobjective sorting-based mutation operators. IEEE Trans Cybern 44(12):2792–2805CrossRef Wang J, Liao J, Zhou Y et al (2014) Differential evolution enhanced with multiobjective sorting-based mutation operators. IEEE Trans Cybern 44(12):2792–2805CrossRef
Zurück zum Zitat Yin X, Germay N (1993) A fast genetic algorithm with sharing scheme using cluster analysis methods in multimodal function optimization. In: Artificial Neural Networks and Genetic Algorithms, pp 450–457 Yin X, Germay N (1993) A fast genetic algorithm with sharing scheme using cluster analysis methods in multimodal function optimization. In: Artificial Neural Networks and Genetic Algorithms, pp 450–457
Zurück zum Zitat Yu WJ, Shen M, Chen WN et al (2014) Differential evolution with two-level parameter adaptation. IEEE Trans Cybern 44(7):1080–1099CrossRef Yu WJ, Shen M, Chen WN et al (2014) Differential evolution with two-level parameter adaptation. IEEE Trans Cybern 44(7):1080–1099CrossRef
Zurück zum Zitat Zaharie D (2009) Influence of crossover on the behavior of differential evolution algorithm. Appl Soft Comput 9(3):1126–1138CrossRef Zaharie D (2009) Influence of crossover on the behavior of differential evolution algorithm. Appl Soft Comput 9(3):1126–1138CrossRef
Zurück zum Zitat Zhai Z, Li X (2011) A dynamic archive based niching particle swarm optimizer using a small population size. In: Proceedings of the Australian Computer Science Conference (ACSC 2011), ACM, pp 1–7 Zhai Z, Li X (2011) A dynamic archive based niching particle swarm optimizer using a small population size. In: Proceedings of the Australian Computer Science Conference (ACSC 2011), ACM, pp 1–7
Zurück zum Zitat Zhang H, Yue D, Xie X et al (2015) Multi-elite guide hybrid differential evolution with simulated annealing technique for dynamic economic emission dispatch. Appl Soft Comput 34:312–323CrossRef Zhang H, Yue D, Xie X et al (2015) Multi-elite guide hybrid differential evolution with simulated annealing technique for dynamic economic emission dispatch. Appl Soft Comput 34:312–323CrossRef
Zurück zum Zitat Zhang G, Li D, Zhou X, et al (2015) Differential evolution with dynamic niche radius strategy for multimodal optimization. In: The 27th international conference on control and decision conference (CCDC 2015), IEEE, pp 3059–3064 Zhang G, Li D, Zhou X, et al (2015) Differential evolution with dynamic niche radius strategy for multimodal optimization. In: The 27th international conference on control and decision conference (CCDC 2015), IEEE, pp 3059–3064
Zurück zum Zitat Zhang JQ, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evolut Comput 13(5):945–958CrossRef Zhang JQ, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evolut Comput 13(5):945–958CrossRef
Zurück zum Zitat Zhu W, Fang JA, Tang Y et al (2012) Digital IIR filters design using differential evolution algorithm with a controllable probabilistic population size. PloS One 7(7):e40549CrossRef Zhu W, Fang JA, Tang Y et al (2012) Digital IIR filters design using differential evolution algorithm with a controllable probabilistic population size. PloS One 7(7):e40549CrossRef
Metadaten
Titel
New mutation strategies of differential evolution based on clearing niche mechanism
verfasst von
Yanan Li
Haixiang Guo
Xiao Liu
Yijing Li
Wenwen Pan
Bing Gong
Shaoning Pang
Publikationsdatum
29.08.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 20/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-016-2318-4

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