An intensify Harris Hawks optimizer for numerical and engineering optimization problems

Recently developed Harris Hawks Optimization has virtuous behavior for finding optimum solution in search space. However, it easily get trapped into local search space for constrained engineering optimization problems. In order to accelerate the global search phase of existing Harris Hawks optimizer and to stuck it out of local search space, the proposed research aims to explore the exploration phase of the existing optimizer, the hybrid variant of Harris Hawks optimizer has been developed using sinecosine algorithm and named as Hybrid Harris Hawks-Sine Cosine Algorithm (hHHO-SCA) The effectiveness of the proposed optimizer has been tested for various nonlinear, non-convex and highly constrained engineering design problem. In order to validate the results of the proposed algorithm, 65 standard benchmark problems including CEC2017, CEC2018 and eleven multidisciplinary engineering design optimization problems has been taken into consideration. After verification it has been observed that the outcomes of the proposed hHHO-SCA optimization algorithm is much better than standard sine-cosine optimization algorithm, Harris Hawks Optimizer, Ant Lion Optimizer algorithm, Moth Flame Optimization algorithm, grey wolf optimizer algorithm, and others recently described metaheuristics, heuristics and hybrid type optimization search algorithm and proposed algorithm endorses its effectiveness in multi-disciplinary design and engineering optimization problems. (C) 2019 Elsevier B.V. All rights reserved.