Open AccessANALYSIS OF MODERN TECHNIQUES FOR SOFTWARE OPTIMIZATION
Author(s) -
Biobele Ojekudo Okardi,
Nathaniel Akofure
Publication year - 2021
Publication title -
international journal of computer science and mobile computing
Language(s) - English
Resource type - Journals
ISSN - 2320-088X
DOI - 10.47760/ijcsmc.2021.v10i07.007
Subject(s) - ant colony optimization algorithms , metaheuristic , simulated annealing , computer science , meta optimization , engineering optimization , genetic algorithm , multi swarm optimization , optimization problem , mathematical optimization , software , artificial bee colony algorithm , test functions for optimization , artificial intelligence , machine learning , algorithm , mathematics , programming language
Traditional Methods of optimization have failed to meet up the rapid changing world in the demand of high quality and accuracy in solution delivery. Optimization literally means looking for the best possible or most desired solution to a problem. Optimization techniques are basically classified into three groups, namely; the Traditional Method, Artificial Intelligent Method, and Hybrid Artificial Intelligent technique. In this paper, an attempt is made to review literatures on different modern optimization techniques for application in various disciplines. A general review was made on some of the modern optimization methods such as Genetic Algorithm, Ant colony method, Honey Bee optimization method, and Simulated Annealing optimization.