Evolutionary Constrained Optimization by Rituparna Datta & Kalyanmoy Deb

Author:Rituparna Datta & Kalyanmoy Deb
Language: eng
Format: epub
Publisher: Springer India, New Delhi

In the estimated comparison, the approximation values are compared first. When a value is worse than the other value, the estimated comparison returns an estimated result without evaluating the true function. When it is difficult to judge the result from the approximation values, true values are obtained by evaluating the true function and the estimated comparison returns a true result based on the true values. Using the estimated comparison, the evaluation of the true function is sometimes omitted and the number of function evaluations can be reduced.

In this chapter, the estimated comparison is applied to constrained optimization and DE, which is a combination of the constrained method and the estimated comparison (Takahama and Sakai 2013) using a potential model defined and improved by approximating not only the objective function but also the constraint violation. The potential model without learning process is adopted as a rough approximation model (Takahama and Sakai 2008b). DE is an efficient constrained optimization algorithm that can find near-optimal solutions in a small number of function evaluations. The effectiveness of DE is shown by solving well-known 13 constrained problems mentioned in Coello (2002) and comparing the results of DE with those of representative methods. It is shown that DE can solve problems with a much smaller, about half, number of function evaluations compared with the representative methods.

In Sect. 6.2, constrained optimization methods and approximation methods are reviewed. The constrained method and the estimated comparison using the potential model are explained in Sects. 6.3 and 6.4, respectively. The DE is described in Sect. 6.5. In Sect. 6.6, experimental results on 13 constrained problems are shown and the results of DE are compared with those of other methods. Finally, conclusions are described in Sect. 6.7.

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.