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Status: Unchecked ×Keyword: gear train design ×Clear all

3 claims from 1 paper

1. Computer Science › Metaheuristic Optimization Algorithms Research

   Development and evaluation of hybrid harris hawks optimization algorithms for advanced engineering applications

   Sharma, Bharali, Motghare, Arora, Yoon and Joshi · Scientific Reports · 2025

   The paper builds seven hybrid versions of the Harris Hawks Optimizer and tests them on benchmark functions and engineering design problems against other optimisers, reporting better accuracy and speed.

   Unchecked3 claims
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   1. UncheckedTwo hybrid Harris Hawks variants, HHO-PSO and HHO-Elite, reached up to 35% faster convergence and far smaller solution values than classical baselines.“HHO-PSO and HHO-Elite achieved up to 35% faster convergence and reached solution values as small as 10⁻ 216 , compared with much weaker values (10⁻ 42 -10⁻ 47 ) for classical baselines.”
   2. UncheckedOn multimodal and fixed-dimension test functions, three Harris Hawks hybrids delayed stagnation and kept diversity, avoiding premature convergence.“On multimodal and fixed-dimension functions, HHO-Elite, HHO-CHAOS, and HHO-ADAP effectively delayed stagnation and preserved diversity, avoiding premature convergence.”
   3. UncheckedOn engineering design problems, the hybrid Harris Hawks algorithms reached near-optimal values for five problems, such as a pressure vessel of about 5885.2.“For engineering problems, the hybrids produced near-optimal designs: pressure vessel (≈5885.2), spring (≈0.01267), welded beam (≈1.7257), gear train (= 0), and Belleville spring (≈1.9795).”