Abstract
Differential evolution is a simple evolutionary algorithm by simulating Darwinian evolution principle where the population of individuals are evolved and adapted with some reproduction mechanisms such as mutation, crossover and selection operator in the computer environment. During a mutation in the nature, only a few vectors of the individuals will be mutated instead of a mutation in whole vectors. Also during a crossover operation, there is still a mutation chance for individuals. This work proposed a novel mutation and crossover operation for multi-objective differential evolution inspired by above, named as NMCO-MODE. In the NMCO-MODE, offspring is allowed to mutate during a crossover as it is same for living individuals in nature, or keep some of its vector same after a mutation. At last, the NMCO-MODE is tested with multi-objective optimization problems (MOP), it’s found out that the new mechanism significantly improved performance of differential evolution algorithm. It has sharp convergence character and gets stuck in local minima less frequently than other multi-objective evolutionary algorithms.
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.
