COOA: Competitive optimization algorithm

Yousef Sharafi*, Mojtaba Ahmadieh Khanesar, Mohammad Teshnehlab

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


This paper presents a novel optimization algorithm based on competitive behavior of various creatures such as birds, cats, bees and ants to survive in nature. In the proposed method, a competition is designed among all aforementioned creatures according to their performances. Every optimization algorithm can be appropriate for some objective functions and may not be appropriate for another. Due to the interaction between different optimization algorithms proposed in this paper, the algorithms acting based on the behavior of these creatures can compete each other for the best. The rules of competition between the optimization methods are based on imperialist competitive algorithm. Imperialist competitive algorithm decides which of the algorithms can survive and which of them must be extinct. In order to have a comparison to well-known heuristic global optimization methods, some simulations are carried out on some benchmark test functions with different and high dimensions. The obtained results shows that the proposed competition based optimization algorithm is an efficient method in finding the solution of optimization problems.

Original languageEnglish
JournalSwarm and Evolutionary Computation
Pages (from-to)39-63
Number of pages25
Publication statusPublished - 1 Oct 2016
Externally publishedYes


  • Ant colony optimization
  • Artificial bee colony optimization
  • Cat swarm optimization
  • Function optimization
  • Imperialist competitive algorithm
  • Particle swarm optimization
  • Swarm intelligence

Cite this