hypDE: A Hyper-Heuristic Based on Differential Evolution for Solving Constrained Optimization Problems
In this paper, we present a hyper-heuristic, based on Differential Evolution, for solving constrained optimization problems. Differential Evolution has been found to be a very effective and efficient optimization algorithm for continuous search spaces, which motivated us to adopt it as our search engine for dealing with constrained optimization problems. In our proposed hyper-heuristic, we adopt twelve differential evolution models for our low-level heuristic.We also adopt four selection mechanisms for choosing the low-level heuristic. The proposed approach is validated using a well-known benchmark for constrained evolutionary optimization. Results are compared with respect to those obtained by a state-of-theart constrained differential evolution algorithm (CDE) and another hyper-heuristic that adopts a random descent selection mechanism. Our results indicate that our proposed approach is a viable alternative for dealing with constrained optimization problems.
KeywordsTest Problem Differential Evolution Selection Mechanism Constrain Optimization Problem Differential Evolution Algorithm
Unable to display preview. Download preview PDF.
- 2.Burke, E., Hart, E., Kendall, G., Newall, J.: Hyper-Heuristics: An Emerging Direction In Modern Search Technology, handbook of metaheuristics edn., ch. 16, pp. 457–474. Springer, New York (2003)Google Scholar
- 4.Chakhlevitch, K., Cowling, P.: Hyperheuristics: Recent Developments. SCI, vol. 136, pp. 3–29. Springer, Berlin (2008)Google Scholar
- 6.De Jong, K.A.: An analysis of the behaviour of a class of genetic adaptive systems. Ph.D. thesis, University of Michigan (1975)Google Scholar
- 7.Fan, Z., Liu, J., Sorensen, T., Wang, P.: Improved differential evolution based on stochastic ranking for robust layout synthesis of mems components. IEEE Transactions On Industrial Electronics 56(4), 937–948 (2008)Google Scholar
- 9.Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco (2001)Google Scholar
- 10.Lampinen, J.: Constraint handling approach for the differential evolution algorithm. In: Proceedings of the Congress on Evolutionary Computation 2002 (CEC 2002), vol. 2, pp. 1468–1473. IEEE Service Center, Piscataway (2002)Google Scholar
- 11.Price, K.: An introduction to differential evolution. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 79–106. McGraw-Hill (1999)Google Scholar
- 13.Schwefel, H.P.: Evolution and Optimum Seeking. John Wiley & Sons, New York (1995)Google Scholar
- 15.Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Tech. Rep. TR-95-012, International Computer Science Institute (1995)Google Scholar