A Novel Deluge Swarm Algorithm for Optimization Problems

In this study, a novel population based algorithm which is based on great deluge, is presented for solving optimization problems. Optimization problems due to the vast application in real life and science are so important. By applying more limitation they are classified as NP-hard problems. NP-hard problems, because of high complexity, can be solved by Meta-heuristic methods. In this regards population-based approaches are considered as a good option.According to the proposed algorithm mechanism, local and global search can be done. Some of the advantages of this algorithm include simplicity, avoid trapping in local optima, appropriate balance between local and global search. The approach is examined on standard functions. Ackley and sphere, for instance are taking into account. The results are compared with G-PSO, G-HS, GSA, CM-AFSA and M-ABC which in all cases proposed algorithm shows better results

Keywords:

Deluge Swarm algorithm , Optimization , NP-hard problems