aRoyal Institute of Technology and Science, Chevella, Hyderabad, India. E-mail: informraziuddin@gmail.com, syed49in@yahoo.com.
bFranklin Templeton Investments India Ltd., Hyderabad, India. E-mail: khazi.abdullateef@yahoo.com.
cGitam Institute of Technology, Gitam University, Vizag, India. E-mail: rdavuluri@yahoo.com.
The Bioinspired Computational (BC) algorithms are the outcome of extraction of natural phenomenon for problem solving. Different BC algorithms have shown promising results on certain problems and worst on other. The objective of this paper is to investigate and analyze Bioinspired Computational (BC) algorithms on complex multimodal optimization problems. Accordingly, special attention will be directed to the Evolutionary Algorithms (EA) and Swarm Intelligence (SI). The comprehensive analysis of different BC Algorithms is carried out on a set of standard complex benchmark problems with 10, 30 and 50 dimensions. The algorithmic suitability, robustness and convergence rate of each will be investigated. Finally the current trends in this area are discussed and some possible paths for further research are addressed.
Evolutionary Algorithm, Swarm Intelligence, Multimodal
