An Improved Harris Hawks Optimization (HHO) Algorithm

Harris hawks optimization is a recently introduced optimization algorithm motivated form the killer nature of bird called Harris hawks. They kill their prey using different strategies depending upon the escaping energy of prey. They usually hunt in packs of two to six hawks. In this paper, three mechanisms are proposed to improve the performance of algorithm. In First approach, Roulette wheel (RW) based selection mechanism is utilized to select the candidate (Harris hawks) form the population instead of random selection Harris hawks. This selection technique is used instead of randomly choosing Harris hawks form the population in the exploration phase of algorithm. Basically Roulette wheel mechanism is used for indexing of Harris hawks. In Second approach, the equation which shows the decreasing pattern of energy of rabbit is changed and new equation is proposed. This equation plays the important role in HHO algorithm as it makes the balance between the exploration and exploitation of algorithm. This shows the great impact on the performance of algorithm. In Third approach, new energy equation is incorporated with roulette wheel selection mechanism for more improvement. The implementation of the proposed Improved Harris hawks optimization (HHO-I, HHO-II, HHO-III) is evaluated on 23 standard benchmarks (unimodal and multimodal) and compared with other well-popular algorithms are GWO, SCA, WOA, PSO and original HHO. .