A Study on Evolutionary Algorithms and Its Applications

Abstract

. Evolutionary methods are a horror-based approach to solving problems that are not easily solved in polynomial time, for example, classical NP-heart problems and take longer to complete. Evolutionary methods are commonly used to provide good approximate solutions to problems that cannot be easily solved using other techniques. Many optimization issues fall into this category. It can be very calculated- finding a suitable solution is serious but sometimes the optimal solution is enough. Major classes of contemporaries (in the order of popularity) E.A. Genetic algorithms (GAs), evolutionary strategies (ESs), differential evolution (DE) and distribution algorithm evaluation (EDAs) are used. Evolutionary methods are based on the concepts of biological evolution. The 'population' of possible solutions to the problem will be created first, and each solution will be evaluated using a 'fitness function'. The population develops over time and (hopefully) identifies the best solutions.