A Preference-based Stepping ahead Artificial Bee Colony Algorithm for Global Optimization

Abstract

Information systems are nowadays more inclined towards using Artificial Intelligence to improve and evolve. One area that provides the solution for improvement in terms of efficiency is optimization. Optimization problems are everywhere and the complexity is increasing, therefore, more intelligent approaches are needed. An intelligent approach that has shown promising results in solving real-world problems is the artificial bee colony (ABC) algorithm. In this paper, the ABC algorithm is modified with a novel technique called stepping ahead. The proposed method is called the preference-based stepping ahead Artificial Bee Colony (ABC-Step) Algorithm. The algorithm takes advantage of the best solution to find solutions more superior through better exploitation of the search space. The proposed algorithm is tested and validated on a set of 20 benchmark global optimization functions together with performance analysis on popular metaheuristics algorithms. ABC-Step provides competitive results to the compared algorithms from the literature and the ABC algorithm