A Novel Hybrid ASO-NM Algorithm and Its Application to Automobile Cruise Control System

Abstract

A novel hybrid algorithm developed by merging atom search optimization (ASO) and Nelder-Mead (NM) simplex search algorithms is presented. The proposed improved algorithm (ASO-NM) is the first reported work on combining ASO and NM methods for optimization problems. The combination of ASO and NM leads to the construction of the desired metaheuristic approach that has a balanced exploration and exploitation. The proposed hybrid ASO-NM was used for optimizing a proportional-integral-derivative controller design for automobile cruise control systems as well as testing four well-known classical benchmark functions for the first time. The obtained statistical and transient response analyses and comparisons have shown the better capability of the proposed hybrid ASO-NM algorithm which can be used for further optimization problems as an effective approach.