An improved Chaotic Harris Hawks Optimizer for solving numerical and engineering optimization problems

Harris Hawk's Optimizer (HHO) is a recently developed meta-heuristics search algorithm with inherent capability to explore global minima and maxima. However, the local search of the basic HHO algorithm is sluggish and has slow convergence rate due to its poor exploitation capability. In the present work, exploration and exploitation phase of HHO have been improved using a chaotic variant of the present optimizer. The proposed chaotic variant has been simulated and tested for 23 standard test functions and 10 different engineering design optimization problems of real life. To check the efficacy of the proposed algorithm, the test results of the proposed CHHO algorithm have been compared with others recently developed and well-known classical optimizers, such as PSO, DE, SSA, MVO, GWO, DE, MFO, SCA, CS, TSA, PSO-DE, GA, HS, Ray and Sain, MBA, ACO, MMA, etc. The experimental results reveal that the suggested method outperforms on most of the test functions and engineering design challenges with superior convergence.