Genetic Programming and Evolvable Machines

, Volume 14, Issue 4, pp 395–427

A high performance genetic algorithm using bacterial conjugation operator (HPGA)

  • Amir Mehrafsa
  • Alireza Sokhandan
  • Ghader Karimian
Article

DOI: 10.1007/s10710-013-9185-x

Cite this article as:
Mehrafsa, A., Sokhandan, A. & Karimian, G. Genet Program Evolvable Mach (2013) 14: 395. doi:10.1007/s10710-013-9185-x

Abstract

In this paper an efficient evolutionary algorithm is proposed which could be applied to real-time problems such as robotics applications. The only parameter of the proposed algorithm is the “Population Size” which makes the proposed algorithm similar to parameter-less algorithms, and the only operator applied during the algorithm execution is the bacterial conjugation operator, which makes using and implementation of the proposed algorithm much easier. The procedure of the bacterial conjugation operator used in this algorithm is different from operators of the same name previously used in other evolutionary algorithms such as the pseudo bacterial genetic algorithm or the microbial genetic algorithm. For a collection of 23 benchmark functions and some other well-known optimization problems, the experimental results show that the proposed algorithm has better performance when compared to particle swarm optimization and a simple genetic algorithm.

Keywords

Evolutionary algorithm Genetic algorithm Bacterial conjugation High performance Real-time Parameter less 

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Amir Mehrafsa
    • 1
  • Alireza Sokhandan
    • 1
  • Ghader Karimian
    • 2
  1. 1.School of Engineering Emerging TechnologiesUniversity of TabrizTabrizIran
  2. 2.Faculty of Electrical and Computer EngineeringUniversity of TabrizTabrizIran

Personalised recommendations