SHIODEG: A Hybrid Success History Intelligent Optimization

SHIODEG: A Hybrid Success History Intelligent Optimization Algorithm for Engineering Design Problems

ABSTRACT This paper introduces SHIODEG, a hybrid optimization algorithm that combines a Success History Intelligent Optimizer (SHIO) with Gaussian Transformation (GT) and Differential Evolution (DE). Furthermore, the SHIODEG’s mechanism allows for intelligent exploration of the search space. Subsequently, the GT infuses normally distributed random perturbations, aiding in efficient global search. HIODEG has tested over 65 benchmark functions that represent unimodal and multi-modal functions. Its performance is compared against state-of-the-art optimization algorithms, ensuring a thorough and unbiased assessment of its capabilities. Further, it has been applied to optimize engineering design problems, such as tension/compression springs, welded beams, pressure vessels, speed reducers, three-bar trusses, and cantilever beams. The results show that SHIODEG consistently demonstrated its ability to handle complex, multi-dimensional search spaces adeptly while balancing intricate trade-offs between cost, efficiency, and reliability.