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Comparison of Hybrid Elephant Herding Optimization with Different Evolutionary Optimization Algorithms
Many optimization algorithms that imitate the social behaviour of animals and natural biological evolution have been proposed in the recently preceding years. These nature inspired algorithms known as evolutionary algorithms have considerably enhanced the development of the optimization process. In this paper, a hybrid elephant herding opposition algorithm is proposed and a comparative study is conducted to analyse the effectiveness of the proposed algorithm. For the purpose of the comparison, the optimization algorithms that have been taken up for the study are Refined Selfish Herd Optimization (RSHO), Spotted Hyena Optimization (SHO), Chicken Swarm Optimization (CSO) and Particle Swarm Optimization (PSO). Tests on 21 common benchmark functions have been conducted to evaluate the performance of the proposed algorithm. The results from the experiment concluded that the proposed algorithm performs better than the other algorithms.
Evolutionary Algorithm, Elephant Herding Optimization, Benchmark Functions.
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