A Shuffle-Based Artificial Bee Colony Algorithm for Solving Integer Programming and Minimax Problems

The artificial bee colony (ABC) algorithm is a prominent swarm intelligence technique due to its simple structure and effective performance. However, the ABC has slow convergence rate when it used solve complex optimization problems since solution search equation more of an exploration than exploitation operator. This paper presents improved for solving integer programming minimax problems. proposed approach employs modified operator, which exploits useful information current best in onlooker phase with intention improving tendency. Furthermore, shuffle mutation operator applied created solutions both phases help achieve better balance between global local abilities provide valuable speed. experimental results, obtained by testing on seven ten problems, show that overall performance superior ABC. Additionally, obtains competitive results compared other state-of-the-art algorithms.