Cited By
View all- Hoseinpour ALahijani MHoseinpour MKazemitabar J(2018)Fitness function improvement of evolutionary algorithms used in sensor network optimisationsIET Networks10.1049/iet-net.2017.02517:3(91-94)Online publication date: May-2018
Given an optimization problem, local search algorithms may fail to reach optimal solutions when faced to difficult and unsuitable fitness landscapes. Climbing based optimization is sensitive to unexpected distribution of local optima. In this ...
Cultural learning allows individuals to acquire knowledge from others through non-genetic means. The effect of cultural learning on the evolution of artificial organisms has been the focus of much research. This paper examines the effects of cultural ...
Exploration and exploitation are two complementary aspects of Evolutionary Algorithms. Exploration, in particular, is promoted by specific diversity keeping mechanisms generally relying on the genotype or the fitness value. Recent works suggest that, in ...
Association for Computing Machinery
New York, NY, United States
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in