Solution of Unconstrained Non-Linear Programming Problems using Differential evolution, Genetic algorithm and Artificial bee colony evolutionary algorithms: A comparative study

Abstract

Evolutionary computation (EC) is a set of global optimization algorithms inspired by biological evolution. EC techniques, which are based on principle of evolution and survival of the fittest Darwinian Theory. It is a sub-field of Artificial Intelligent techniques and soft computing. In Evolutionary computation, we use non classical methods based on natural evolution instead of classical methods. When fitness function has several local extreme or not known derivative then it is very difficult to use classical methods for solution of optimization problem in such situation non classical methods gives very convenient and faster solution. In this paper we present Genetic algorithms, Artificial bee colony algorithm and Differential evolution algorithm of Evolutionary computation technique for solution of unconstrained non-linear programming problem. Numerical examples have solved using software MATLAB and the result has compared among evolutionary algorithms as Genetic algorithm, differential algorithm and artificial bee colony algorithm.