Abstract
A novel evolutionary programming algorithm, which not only has a rapid convergence rate but also maintains the diversity of the population so as to escape from local optima, is proposed in this paper. In addition, a multi-modal test function is presented and is used to indicate the efficiency of this algorithm. Several application examples are given to show its usefulness. Scope and purpose Many practical problems can be modeled as optimization problems. In order to solve these optimization problems, many methods have been developed. Inspired by the principles of biological evolution, many simulated evolutionary algorithms have been proposed in literature. This paper presents an efficient evolutionary programming (EP) algorithm and applies it to multi-modal function optimization problems. In addition, two practical examples are presented to show its usefulness. Computer simulation results show that this algorithm provides a possible way for complicated optimization problems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
