Open AccessA Literature Survey on Artificial Swarm Intelligence based Optimization Techniques
Author(s) -
Mr. Gireesha. B
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.5.20205
Subject(s) - ant colony optimization algorithms , metaheuristic , swarm intelligence , parallel metaheuristic , computer science , particle swarm optimization , engineering optimization , artificial bee colony algorithm , multi swarm optimization , heuristic , mathematical optimization , meta optimization , field (mathematics) , artificial intelligence , optimization problem , algorithm , mathematics , pure mathematics
From few decades’ optimizations techniques plays a key role in engineering and technological field applications. They are known for their behaviour pattern for solving modern engineering problems. Among various optimization techniques, heuristic and meta-heuristic algorithms proved to be efficient. In this paper, an effort is made to address techniques that are commonly used in engineering applications. This paper presents a basic overview of such optimization algorithms namely Artificial Bee Colony (ABC) Algorithm, Ant Colony Optimization (ACO) Algorithm, Fire-fly Algorithm (FFA) and Particle Swarm Optimization (PSO) is presented and also the most suitable fitness functions and its numerical expressions have discussed.