The grouping differential evolution algorithm for multi-dimensional optimization problems

Control and Cybernetics

Volumn 39, Issue 2, 2010, Pages 527-550

  Piotrowski, Adam P ^a   Napiórkowski, Jaroslaw J ^a  

^a INSTITUTE OF GEOPHYSICS   (Poland)

Author keywords

Differential evolution; Metaheuristics; Multidimensional problems; Multimodal problems

Indexed keywords

EID: 78650370220     PISSN: 03248569     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (23)

1. ADRIO, E.P. (2005) Multivariate Test Functions Library in C for unconstrained global optimization, http://geocities.com/eadorio/mvf.pdf.
2. ALI, M.M., KHOMPATRAPORN, C and ZABINSKY, Z.B. (2005) A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems. Journal of Global Optimization 31, 635-672.
3. ALI, M.M. (2007) Differential Evolution with preferential crossover. European Journal of Operational Research 181, 1137-1147.
4. BREST, J., BOSKOVIC, B., GREINER, S., ZUMER, V. and MAUCEC, M.S. (2007) Performance comparison of Self-Adaptive and Adaptive Differential Evolution algorithms. Soft Computing 11, 7, 617-629.
5. CLERC, M. (2006) Particle Swarm Optimization. ISTE Ltd, London.
6. DAS, S., ABRAHAM, A., CHAKRABORTY, U.K. and KONAR, A. (2009) Differential Evolution Using a Neighborhood-based Mutation Operator. IEEE Transactions on Evolutionary Computations 13, 3, 526-553.
7. GUSTAFSON, S. and BURKE, E.K. (2006) The Speciating Island Model: An alternative parallel evolutionary algorithm. Journal of Parallel and Distributed Computing 66 (8), 1025-1036.
8. HEDDAR, A.R. and FUKUSHIMA, M. (2006) Tabu Search directed by direct search methods for nonlinear global optimization. European Journal of Operational Research 170, 329-349.
9. HOLLAND, J.H. (2000) Building blocks, cohort genetic algorithms and hyperplane - defined functions. Evolutionary Computation 8 (4), 373-391.
10. ILONEN, J., KAMARAINEN, J.K. and LAMPINEN, J. (2003) Differential Evolution training algorithm for feed-foreward neural networks. Neural Processing Letters 17, 93-105.
11. KAELO, P. and ALI, M.M. (2006) A numerical study of some modified Differtential Evolution algorithms. European Journal of Operational Research 169, 1176-1184.
12. Liu, J. and LAMPINEN, J. (2005) A Fuzzy Adaptive Differential Evolution algorithm. Soft Computing 9, 448-462.
13. Liu, Y., YAO, X. and HIGRUCHl, T. (2000) Evolutionary ensembles with negative correlation learning. IEEE Transactions on Evolutionary Computation 4 (4), 380-387. (Pubitemid 32075189)
14. MISHRA, S.K. (2006) Global optimization by Differential Evolution and Particle Swarm methods evaluation on some benchmark functions. Social Science Research Network, Working Papers Series, http://ssrn.com/ abstract=933827.
15. PRICE, K.V., STORN, R.M. and LAMPINEN, J.A. (2005) Differential Evolution. A Practical Approach to Global Optimization. Springer-Verlag, Berlin-Heidelberg.
16. QIN, A.K., HUANG, V.L. and SUGANTHAN, P.N. (2009) Differential Evolution algorithm with strategy adaptation for global numerical optimization. IEEE Transactions Evolutionary Computation 13 (2), 398-417.
17. ROWIŃSKI, P.M. and PIOTROWSKl, A. (2008) Estimation of parameters of transient storage model by means of multi-layer perceptron neural networks. Hydrological Sciences Journal 53 (1), 165-178.
18. STORN, R. and PRICE, K.V. (1995) Differential Evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR-95-012, International Computer Sciences Institute, Berkeley, CA, USA.
19. STORN, R. and PRICE, K.V. (1997) Differential Evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11 (1), 341-359.
20. WANG, Y.J. and ZHANG, J.S. (2007) Global optimization by an improved Differential Evolutionary algorithm. Applied Mathematics and Computation 188, 669-680.
21. WHITLEY, D., RANA, S., DZUBERA, J. and MATHIAS, K.E. (1996) Evaluating evolutionary algorithms. Artificial Intelligence 85, 245-276.
22. WHITLEY, D., LUNACEK, M. and KNIGHT, J. (2004) Ruffled by Ridges: How Evolutionary Algorithms Can Fail. In: LNCS 3103, Springer, Berlin-Heidelberg.
23. TAO, J. and WANG, N. (2007) DNA computing based RNA genetic algorithm with applications in parameter estimation of chemical engineering processes. Computers and Chemical Engineering 31, 1602-1618.