A comparative investigation of eight recent population-based optimisation algorithms for mechanical and structural design problems - Yıldız, Betül Sultan (Inderscience Enterprises Ltd, 2017)
Nowadays, designing of light-weight components is a very critical issue needed to be solved in industry. Different optimisation techniques have been developed to design light-weight components. In this research, a comparison of population-based optimisation algorithms for optimal design is presented. Additionally, a hybrid interior search-hill climbing algorithm is developed for optimising mechanical and structural design problems such as tension spring problem, welded beam problem, pressure vessel problem and optimal design of a vehicle sliding door hinge. It is shown that the result of the hybrid interior search algorithm (H-ISA) is better than gravitational search algorithm (GSA), ant lion optimiser (ALO), firefly algorithm (FFA), bat algorithm (BAT), league championship algorithm (LCA), symbiotic organisms search (SOS), imperialist competitive algorithm (ICA) and charged system search algorithm (CSS).
Keywords: interior search algorithm; hill-climbing; optimisation