Buoyancy energy driven archimedes optimization algorithm based on Lévy flight and tangent flight

Abstract

Archimedes optimization algorithm (AOA) is a metaheuristic algorithm inspired by the Archimedes physical law. It simulates the principle of buoyancy applied upward to partially or completely submerged objects. The decay energy of buoyancy, Lévy flight and Tangent flight are introduced into AOA. The buoyancy energy is adopted as the judgment condition of global search and local search. Then the location updating methods based on Lévy flight and Tangent flight are proposed so as to enhance its ergodicity and unrepeatable, improve the convergence speed and accuracy. Finally, through a large number of simulation experiments on 25 benchmark functions in CEC-BC-2017, the improved AOAs are compared to show their advantages and disadvantages. On the other hand, two engineering design problems (pressure vessel design and spring design problem) are optimized. The experimental results show that the AOA based on buoyancy energy mixed Lévy flight and Tangent flight can solve the function optimization and engineering optimization problems well. It has the strong balance between exploration and exploitation, fast convergence speed and high search accuracy.