Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems
The proposed technique uses the power of global and local searching from HMCR and PAR parameters. The proposed technique has been tested on 15 standard benchmark functions and compared with existing techniques. The performance of proposed technique is least affected even when the benchmark function is corrupted with noise as compared to other existing techniques. The proposed technique provides better results than the other techniques in noisy and scalable environment. The effect of harmony memory size has also investigated on proposed technique.
harmony search algorithm optimization metaheuristic benchmark problems data clustering