Testing Multiple Strategy Human Optimization based Artificial Human Optimization Algorithms

  • Satish Gajawada Hyderabad, India
  • Hassan M. H. Mustafa
Keywords: Artificial Humans, Global Optimization Techniques, Artificial Human Optimization, Nature Inspired Computing, Bio-Inspired Computing, Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Evolutionary Computing

Abstract

Recently a new trend titled ‘Artificial Human Optimization’ has become popular in Evolutionary Computing Domain. More than 30 papers were published in this new field proposed in December 2016. ‘Hassan Satish Particle Swarm Optimization (HSPSO)’ and ‘Human Inspired Differential Evolution (HIDE)’ are the two latest Artificial Human Optimization algorithms proposed based on Multiple Strategy Human Optimization. In this paper we focus on Testing HSPSO and HIDE by applying these latest algorithms on Ackley, Bohachevsky, Booth, Three-Hump Camel and Beale benchmark functions. Results obtained for these Artificial Human Optimization Algorithms are compared with Differential Evolution and Particle Swarm Optimization.

References

Satish Gajawada, “Artificial Human Optimization – An Introduction”, Transactions on Machine Learning and Artificial Intelligence, Volume 6, No 2, pp: 1-9, April 2018.

Satish Gajawada, Hassan M. H. Mustafa , HIDE : Human Inspired Differential Evolution - An Algorithm under Artificial Human Optimization Field , International Journal of Research Publications (Volume: 7, Issue: 1), http://ijrp.org/paper_detail/264

Satish Gajawada and Hassan M. H. Mustafa, Hybridization concepts of Artificial Human Optimization field Algorithms incorporated into Particle Swarm Optimization (In Progress).

https://www.sfu.ca/~ssurjano/ackley.html (accessed 28th July, 2018)

Published
2018-08-29
Section
Research Articles