Self-adaptive differential evolution algorithm using population size reduction and three strategies

Soft Computing

Volumn 15, Issue 11, 2011, Pages 2157-2174

  Brest, Janez ^a   Maučec, Mirjam Sepesy ^a  

^a UNIVERSITY OF MARIBOR   (Slovenia)

Author keywords

Differential evolution; Large scale optimization; Multiple statistical comparison; Self adaptation

Indexed keywords

BENCH-MARK PROBLEMS; CONTINUOUS OPTIMIZATION; CONTINUOUS OPTIMIZATION PROBLEMS; CONTINUOUS VARIABLES; DIFFERENTIAL EVOLUTION; GLOBAL SEARCH; LARGE-SCALE OPTIMIZATION; META HEURISTICS; MULTIPLE COMPARISON; NON-PARAMETRIC; OPTIMIZATION ALGORITHMS; POPULATION SIZES; REAL-WORLD OPTIMIZATION; SELF ADAPTATION; SELF-ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHMS; STATISTICAL COMPARISONS;

ADAPTIVE ALGORITHMS; OPTIMIZATION; POPULATION STATISTICS; PROBLEM SOLVING; SIZE DETERMINATION;

EVOLUTIONARY ALGORITHMS;

EID: 80053941705     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-010-0644-5     Document Type: Article

References (50)

1. Auger A, Hansen N (2005) A restart CMA evolution strategy with increasing population size. In: Proceedings of the 2005 IEEE Congress on evolutionary computation, IEEE Press, pp 1769-1776.
2. van den Bergh F, Engelbrecht AP (2004) A cooperative approach to particle swarm optimisation. IEEE Trans Evol Comput 3: 225-239.
3. Brest J (2009) Constrained real-parameter pptimization with ε-self-adaptive differential evolution. Stud Comput Intell. ISBN: 978-3-642-00618-0 198: 73-93.
4. Brest J, Maučec MS (2008) Population size reduction for the differential evolution algorithm. Appl Intell 29(3): 228-247.
5. Brest J, Greiner S, Bošković B, Mernik M, Žumer V (2006a) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6): 646-657.
6. Brest J, Žumer V, Maučec MS (2006b) Self-adaptive differential evolution algorithm in constrained real-parameter optimization. In: The 2006 IEEE Congress on evolutionary computation CEC 2006, IEEE Press, pp 919-926.
7. Brest J, Bošković B, Greiner S, Žumer V, Maučec MS (2007) Performance comparison of self-adaptive and adaptive differential evolution algorithms. Soft Comput Fusion Found Methodol Appl 11(7): 617-629.
8. Brest J, Zamuda A, Bošković B, Maučec MS, Žumer V (2008) High-dimensional real-parameter optimization using self-adaptive differential evolution algorithm with population size reduction. In: 2008 IEEE World Congress on computational intelligence, IEEE Press, pp 2032-2039.
9. Brest J, Zamuda A, Bošković B, Maučec MS, Žumer V (2009) Dynamic optimization using self-adaptive differential evolution. In: IEEE Congress on evolutionary computation (CEC) 2009, IEEE Press, pp 415-422.
10. Brest J, Zamuda A, Bošković B, Fister I, Maučec MS (2010) Large scale global optimization using self-adaptive differential evolution algorithm. In: IEEE World Congress on computational intelligence, pp 3097-3104.
11. Caponio A, Neri F, Tirronen V (2009) Super-fit control adaptation in memetic differential evolution frameworks. Soft Comput Fusion Found Methodol Appl 13(8): 811-831.
12. Das S, Abraham A, Chakraborty U, Konar A (2009) Differential evolution using a neighborhood-based mutation operator. IEEE Trans Evol Comput 13(3): 526-553.
13. Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7: 1-30.
14. Dunn OJ (1961) Multiple comparisons among means. J Am Stat Assoc 56(293): 52-64.
15. Eshelman LJ, Schaffer JD (1993) Real-coded genetic algorithms and interval-schemate. In: Whitley LD (ed) Foundations of genetic algorithms, vol 2. Morgan Kaufmann Publishers, USA, pp 187-202.
16. Feoktistov V (2006) Differential evolution: in search of solutions (Springer optimization and Its applications). Springer, New York.
17. Gao Y, Wang YJ (2007) A memetic differential evolutionary algorithm for high dimensional functions' optimization. Int Conf Nat Comput 4: 188-192. doi: 10. 1109/ICNC. 2007. 60.
18. García S, Herrera F (2008) An extension on statistical comparisons of classifiers over multiple data sets for all pairwise comparisons. J Mach Learn Res 9: 2677-2694.
19. García S, Molina D, Lozano M, Herrera F (2009) A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC 2005 Special Session on Real Parameter Optimization. Journal of Heuristic 15(6): 617-644.
20. García S, Fernández A, Luengo J, Herrera F (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. Info Sci 180(10): 2044-2064.
21. Liu Y, Yao X, Zhao Q, Higuchi T (2001) Scaling up fast evolutionary programming with cooperative coevolution. In: Proceedings of the 2001 Congress on evolutionary computation CEC 2001, IEEE Press, COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea, pp 1101-1108. http://citeseer.ist.psu.edu/liu01scaling.html.
22. MacNish C (2007) Towards unbiased benchmarking of evolutionary and hybrid algorithms for real-valued optimisation. Connect Sci 19(4): 225-239.
23. Mladenovic N, Drazic M, Kovacevic-Vujcic V, Cangalovic M (2008) General variable neighborhood search for the continuous optimization. Eur J Oper Res 191(3): 753-770.
24. Molina D, Lozano M, Herrera F (2009a) Memetic algorithm with local search chaining for continuous optimization problems: a scalability test. In: Proceedings of the ninth international conference intelligent systems design and applications computation, IEEE Press, pp 1068-1073.
25. Molina D, Lozano M, Herrera F (2009b) Memetic algorithm with local search chaining for large scale continuous optimization problems. In: Proceedings of the 2009 IEEE Congress on evolutionary computation, CEC '09, pp 830-837.
26. Muelas S, LaTorre A, Penã JM (2009) A memetic differential evolution algorithm for continuous optimization. In: Proceedings of the ninth international conference intelligent systems design and applications computation, IEEE Press, pp 1080-1084.
27. Neri F, Tirronen V (2010) Recent advances in differential evolution: a survey and experimental analysis. Artif Intell Rev 33(1-2): 61-106.
28. Potter MA, De Jong K (1994) A cooperative coevolutionary approach to function optimization. In: Davidor Y, Schwefel HP, Männer R (eds) Parallel problem solving from nature, PPSN III, Springer, Berlin, pp 249-257. http://citeseer.ist.psu.edu/potter94cooperative.html.
29. Price KV, Storn RM, Lampinen JA (2005) Differential evolution: a practical approach to global optimization. Springer, Berlin.
30. Qin AK, Suganthan PN (2005) Self-adaptive differential evolution algorithm for numerical optimization. In: The 2005 IEEE Congress on evolutionary computation CEC 2005, vol 2, IEEE Press, pp 1785-1791.
31. Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13(2): 398-417.
32. Rahnamayan S, Tizhoosh H, Salama M (2008) Opposition-based differential evolution. IEEE Trans Evol Comput 12(1): 64-79.
33. Rönkkönen J, Kukkonen S, Price KV (2005) Real-parameter optimization with differential evolution. In: The 2005 IEEE Congress on evolutionary computation CEC 2005, vol 1, IEEE Press, pp 506-513.
34. Sofge D, De Jong K, Schultz A (2002) A blended population approach to cooperative coevolution for decomposition of complex problems. In: Proceedings of the 2002 Congress on evolutionary computation (CEC 2002), IEEE, pp 413-418.
35. Storn R, Price K (1995) Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Tech. Rep. TR-95-012, Berkeley, CA. http://citeseer.ist.psu.edu/article/storn95differential.html.
36. Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11: 341-359.
37. Tang K, Yao X, Suganthan PN, MacNish C, Chen YP, Chen CM, Yang Z (2007) Benchmark functions for the CEC 2008 Special Session and Competition on High-Dimenasional Real-Parameter Optimization. Technical report, Nature Inspired Computation and Applications Laboratory, USTC, China. http://nical.ustc.edu.cn/cec08ss.php.
38. Tang K, Li X, Suganthan PN, Yang Z, Weise T (2009) Benchmark functions for the CEC 2010 Special Session and Competition on Large Scale Global Optimization. Technical report, Nature Inspired Computation and Applications Laboratory, USTC, China.
39. Teng N, Teo J, Hijazi M (2009) Self-adaptive population sizing for a tune-free differential evolution. Soft Comput Fusion Found Methodol Appl 13(7): 709-724.
40. Teo J (2006) Exploring dynamic self-adaptive populations in differential evolution. Soft Comput Fusion Found Methodol Appl 10(8): 673-686.
41. Wang Y, Li B (2008) A restart univariate estimation of distribution algorithm: sampling under mixed Gaussian and Lévy probability distribution. In: 2008 IEEE World Congress on computational intelligence, IEEE Press, pp 3917-3924.
42. Yang Z, Tang K, Yao X (2007) Differential evolution for high-dimensional function optimization. In: Srinivasan D, Wang L (eds) 2007 IEEE Congress on evolutionary computation, IEEE computational intelligence society, IEEE Press, pp 3523-3530.
43. Yang Z, Tang K, Yao X (2008a) Large scale evolutionary optimization using cooperative coevolution. Info Sci 178(15): 2985-2999.
44. Yang Z, Tang K, Yao X (2008b) Multilevel cooperative coevolution for large scale optimization. In: Proc. IEEE World Congress on computational intelligence (WCCI 2008), IEEE Press, pp 1663-1670.
45. Yang Z, Tang K, Yao X (2008c) Self-adaptive differential evolution with neighborhood search. In: 2008 IEEE World Congress on computational intelligence evolutionary computation, IEEE Press, pp 1110-1116.
46. Zaharie D (2002) Critical values for the control parameters of differential evolution algorithms. In: Proc. of Mendel 2002, 8th international conference on soft computing, pp 62-67.
47. Zamuda A, Brest J, Boskovic B, Zumer V (2008) Large scale global optimization using differential evolution with self-adaptation and cooperative co-evolution. In: 2008 IEEE World Congress on computational intelligence, IEEE Press, pp 3719-3726.
48. Zar JH (1999) Biostatistical analysis. Prentice-Hall, Englewood Cliffs.
49. Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5): 945-958.
50. Zhao SZ, Liang JJ, Suganthan PN, Tasgetiren MF (2008) Dynamic multi-swarm particle swarm optimizer with local search for large scale global optimization. In: 2008 IEEE World Congress on computational intelligence, IEEE Press, pp 3845-3852.