Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems

Applied Computational Intelligence and Soft Computing

Volumn 2017, Issue , 2017, Pages

  Mohamed, Ali Wagdy ^a   Almazyad, Abdulaziz S ^b,c  

^a AL YAMAMAH UNIVERSITY   (Saudi Arabia)

^b Cairo University   (Egypt)

^c KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85021968017     PISSN: 16879724     EISSN: 16879732     Source Type: Journal    
DOI: 10.1155/2017/7974218     Document Type: Article

References (49)

1. K. Tang, X. Li, P.N. Suganthan, Z. Yang, and T. Weise, "Benchmark functions for the CEC 2010 special session and competition on large scale global optimization," Tech. Rep., Nature Inspired Computation and Applications Laboratory, USTC, Hefei, China, 2009.
2. K. Tang, X. Yao, P. N. Suganthan et al., "Benchmark functions for the CEC2008 special session and competition on large scale global optimization," Technical Report for CEC 2008 special issue, 2007.
3. A. P. Engelbrecht, Computational Intelligence: An Introduction, Wiley-Blackwell, 2002.
4. R. Storn and K. Price, "Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces," Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, 1997.
5. S. A. El-Quliti, A. H. Ragab, R. Abdelaal et al., "Anonlinear goal programming model for university admission capacity planning with modified differential evolution algorithm," Mathematical Problems in Engineering, vol. 2015, Article ID 892937, 13 pages, 2015.
6. S. A. El-Qulity and A. W. Mohamed, "A generalized national planning approach for admission capacity in higher education: a nonlinear integer goal programming model with a novel differential evolution algorithm," Computational Intelligence and Neuroscience, vol. 2016,Article ID 5207362, 14 pages, 2016.
7. N. Hachicha, B. Jarboui, and P. Siarry, "A fuzzy logic control using a differential evolution algorithm aimed at modelling the financial market dynamics," Information Sciences, vol. 181, no. 1, pp. 79-91, 2011.
8. S. A. El-Quliti and A. W. Mohamed, "A large-scale nonlinear mixed-binary goal programming model to assess candidate locations for solar energy stations: an improved binary differential evolution algorithm with a case study," Journal of Computational and Theoretical Nanoscience, vol. 13, no. 11, pp. 7909-7921, 2016.
9. S. Das and P. N. Suganthan, "Differential evolution: a survey of the state-of-the-art," IEEE Transactions on Evolutionary Computation, vol. 15, no. 1, pp. 4-31, 2011.
10. N.Noman and H. Iba, "Accelerating differential evolution using an adaptive local search," IEEE Transactions on Evolutionary Computation, vol. 12, no. 1, pp. 107-125, 2008.
11. S. Das, A. Abraham, U. K. Chakraborty, and A. Konar, "Differential evolution using a neighborhood-based mutation operator," IEEE Transactions on EvolutionaryComputation, vol. 13, no. 3, pp. 526-553, 2009.
12. J. Lampinen and I. Zelinka, "On stagnation of the differential evolution algorithm," in Proceedings of the Mendel 6th International Conference on Soft Computing, pp. 76-83, Brno, Czech Republic, June 2000.
13. A. W. Mohamed and H. Z. Sabry, "Constrained optimization based on modified differential evolution algorithm," Information Sciences, vol. 194, pp. 171-208, 2012.
14. A.W.Mohamed, H. Z. Sabry, andM. Khorshid, "An alternative differential evolution algorithm for global optimization," Journal of Advanced Research, vol. 3, no. 2, pp. 149-165, 2012.
15. A. K. Qin, V. L. Huang, and P. N. Suganthan, "Differential evolution algorithm with strategy adaptation for global numerical optimization," IEEE Transactions on Evolutionary Computation, vol. 13, no. 2, pp. 398-417, 2009.
16. A. W. Mohamed, "Solving stochastic programming problems using new approach to differential evolution algorithm," Egyptian Informatics Journal, 2016.
17. R.Mallipeddi, P. N. Suganthan, Q. K. Pan, and M. F. Tasgetiren, "Differential evolution algorithm with ensemble of parameters and mutation strategies," Applied Soft Computing, vol. 11, no. 2, pp. 1679-1696, 2011.
18. A. W. Mohamed, "An efficient modified differential evolution algorithm for solving constrained non-linear integer and mixed-integer global optimization problems," International Journal of Machine Learning and Cybernetics, 2015.
19. A.W.Mohamed, "A new modified binary differential evolution algorithm and its applications," Applied Mathematics & Information Sciences, vol. 10, no. 5, pp. 1965-1969, 2016.
20. A. Wagdy Mohamed, H. Z. Sabry, and A. Farhat, "Advanced differential evolution algorithm for global numerical optimization," in Proceedings of the IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE '11), pp. 156-161, Penang, Malaysia, December 2011.
21. A. W. Mohamed, H. Z. Sabry, and T. Abd-Elaziz, "Real parameter optimization by an effective differential evolution algorithm," Egyptian Informatics Journal, vol. 14, no. 1, pp. 37-53, 2013.
22. A. W. Mohamed, "A novel differential evolution algorithm for solving constrained engineering optimization problems," Journal of Intelligent Manufacturing, pp. 1-34, 2017.
23. H.-Y. Fan and J. Lampinen, "A trigonometric mutation operation to differential evolution," Journal of Global Optimization, vol. 27, no. 1, pp. 105-129, 2003.
24. K. V. Price, R. M. Storn, and J. A. Lampinen, Differential Evolution: A Practical Approach to Global Optimization, Natural Computing Series, Springer, New York, NY, USA, 1st edition, 2005.
25. A. M. Potter and K. A. D. Jong, "A cooperative co-evolutionary approach to function optimization," in Proceedings of the 3rd International Conference on Parallel Problem Solving from the Nature, pp. 249-257, Springer, October 1994.
26. Z. Yang, K. Tang, and X. Yao, "Large scale evolutionary optimization using cooperative co-evolution," Information Sciences, vol. 178, no. 15, pp. 2985-2999, 2008.
27. M. N. Omidvar, X. D. Li, and X. Yao, "Cooperative co-evolution with delta grouping for large scale non-separable function optimization," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '10), pp. 1762-1769, 2010.
28. Y. Wang and B. Li, "Two-stage based ensemble optimization for large-scale global optimization," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '10), pp. 4488-4495, Barcelona, Spain, July 2010.
29. Y. Wang and B. Li, "A self-adaptive mixed distribution based uni-variate estimation of distribution algorithm for large scale global optimization," in Nature-Inspired Algorithms for Optimisation, R. Chiong, Ed., vol. 193 of Studies in Computational Intelligence, pp. 171-198, Springer, Berlin, Germany, 2009.
30. Y. Liu, X. Yao, Q. Zhao, and T. Higuchi, "Scaling up fast evolutionary porgramming with cooperative co-evolution," in Proceedings of the IEEE World Congress on Computational Intelligence, pp. 1101-1108, 2001.
31. Z. Yang, K. Tang, and X. Yao, "Differential evolution for highdimensional function optimization," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '07), pp. 3523-3530, IEEE, Singapore, September 2007.
32. Z. Yang, K. Tang, and X. Yao, "Multilevel cooperative coevolution for large scale optimization," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '08), pp. 1663-1670, June 2008.
33. A. Zamuda, J. Brest, B. Bo?sovi?c, and V. ?Zumer, "Large scale global optimization using differential evolution with self-adaptation and cooperative co-evolution," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '08), June 2008.
34. F. van den Bergh and A. P. Engelbrecht, "Acooperative approach to participle swam optimization," IEEE Transactions on Evolutionary Computation, vol. 8, no. 3, pp. 225-239, 2004.
35. K. Koro?sec, K. Tashkova, and J. ?Silc, "The differential ant-stigmergy algorithm for large-scale global optimization," in Proceedings of the IEEE Congress on Evolutionary Computation, pp. 4288-4295, Barcelona, Spain, 2010.
36. J. Brest, A. Zamuda, I. Fister, and M. S. Mau?cec, "Large scale global optimization using self-adaptive differential evolution algorithm," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '10), pp. 3097-3104, July 2010.
37. H.Wang, Z.Wu, S. Rahnamayan, D. Jiang, andD.E. Sequential, "Enhanced by neighborhood search for large scale global optimization," in Proceedings of the IEEE Congress on Evolutionary Computation, pp. 4056-4062, Barcelona, Spain, July 2010.
38. D.Molina,M. Lozano, andF.Herrera, "MA-SW-Chains:memetic algorithm based on local search chains for large scale continuous global optimization," in Proceedings of the 6th IEEE World Congress on Computational Intelligence (WCCI '10)- IEEE Congress on Evolutionary Computation (CEC '10), esp, July 2010.
39. S.-Z. Zhao, P.N. Suganthan, and S.Das, "Dynamicmulti-swarm particle swarmoptimizer with sub-regional harmony search," in Proceedings of the 6th IEEE World Congress on Computational Intelligence (WCCI '10)-IEEE Congress on Evolutionary Computation (CEC '10), July 2010.
40. Y. Wang, Z. Cai, and Q. Zhang, "Differential evolution with composite trial vector generation strategies and control parameters," IEEE Transactions on Evolutionary Computation, vol. 15, no. 1, pp. 55-66, 2011.
41. V. Feoktistov, Differential Evolution, in Search of Solutions, vol. 5, Springer, New York, NY, USA, 2006.
42. J. Ronkkonen, S. Kukkonen, and K. V. Price, "Real parameter optimization with differential evolution," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '05), pp. 506-513, Edinburgh, UK, 2005.
43. J. Brest, S. Greiner, B. Bo?skovi?c, M. Mernik, and V. Zumer, "Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems," IEEE Transactions on Evolutionary Computation, vol. 10, no. 6, pp. 646-657, 2006.
44. M. Weber, F. Neri, and V. Tirronen, "A study on scale factor in distributed differential evolution," Information Sciences, vol. 181, no. 12, pp. 2488-2511, 2011.
45. R. A. Sarker, S. M. Elsayed, and T. Ray, "Differential evolution with dynamic parameters selection for optimization problems," IEEE Transactions on Evolutionary Computation, vol. 18, no. 5, pp. 689-707, 2014.
46. S. M. Elsayed, R. A. Sarker, and D. L. Essam, "An improved self-adaptive differential evolution algorithm for optimization problems," IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 89-99, 2013.
47. A.W.Mohamed, "An improved differential evolution algorithm with triangular mutation for global numerical optimization," Computers and Industrial Engineering, vol. 85, pp. 359-375, 2015.
48. S. Chen, "Locust Swarms for Large Scale Global Optimization for Nonseparable Problems".
49. S. García, D. Molina, M. Lozano, and F. Herrera, "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 Heuristics, vol. 15, no. 6, pp. 617-644, 2009.