Balancing exploration and exploitation by using sequential execution cooperation between artificial bee colony and migrating birds optimization algorithms

Authors : Hasan MAKAS, Nejat YUMUŞAK

Pages : 4935-4956

View : 22 | Download : 9

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :The artificial bee colony insert ignore into journalissuearticles values(ABC); algorithm is a metaheuristic search method inspired by bees` foraging behaviour. With its global search ability in scout bee phase, it can easily escape from local optimum traps in the problem space. Therefore, it is good at exploration. The migrating birds optimization insert ignore into journalissuearticles values(MBO); algorithm is another recent metaheuristic search method. It simulates birds` V flight formation, which minimizes energy consumption during flight. The MBO algorithm achieves a good convergence to the global optimum by using its own unique benefit mechanism. That is, it has a good exploitation capability. This paper aimed to combine the good exploration property of the ABC algorithm and the good exploitation property of the MBO algorithm via a sequential execution strategy. In the proposed method, firstly, the ABC algorithm runs. This enables solutions to escape from local optimum traps and orientates them to the region in which the global optimum exists. Then the MBO algorithm runs. It performs a good convergence to the global optimum. In the proposed method, some variants of the ABC algorithm and some other well-known optimization algorithms were tested via benchmark functions. It was seen in the experiments that the proposed method gave competitive benchmark test results considering both success rates and convergence performances.
Keywords : Migrating birds optimization algorithm, artificial bee colony algorithm, sequential execution, cooperation of algorithms, metaheuristics