Enhanced Directed Differential Evolution Algorithm for Solving Constrained Engineering Optimization Problems

Enhanced Directed Differential Evolution Algorithm for Solving Constrained Engineering Optimization Problems

Ali Wagdy Mohamed (Cairo University, Giza, Egypt), Ali Khater Mohamed (Majmaah University, Al Majmaah, Saudi Arabia), Ehab Z. Elfeky (Cairo University, Giza, Egypt) and Mohamed Saleh (Cairo University, Giza, Egypt)
Copyright: © 2019 |Pages: 28
DOI: 10.4018/IJAMC.2019010101

Abstract

The performance of Differential Evolution is significantly affected by the mutation scheme, which attracts many researchers to develop and enhance the mutation scheme in DE. In this article, the authors introduce an enhanced DE algorithm (EDDE) that utilizes the information given by good individuals and bad individuals in the population. The new mutation scheme maintains effectively the exploration/exploitation balance. Numerical experiments are conducted on 24 test problems presented in CEC'2006, and five constrained engineering problems from the literature for verifying and analyzing the performance of EDDE. The presented algorithm showed competitiveness in some cases and superiority in other cases in terms of robustness, efficiency and quality the of the results.
Article Preview

2. Cops Formulation And Handling The Constraints

Generally, COP has the following form (Yong, 2009):Min , (1) St.:

(2)
(3) “Where , is the feasible region, and is an -dimensional rectangular space in defined by the parametric constraints where and are lower and upper bounds for a decision variable , respectively. Most constraint-handling techniques that’s is used in EAs are dealing with inequality constraints only. Therefore, inequality constraints of the form are obtained from equality constraints, where is the tolerance level.” (Mohamed A. W., 2017)

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 11: 4 Issues (2020): Forthcoming, Available for Pre-Order
Volume 10: 4 Issues (2019): 2 Released, 2 Forthcoming
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing