Hybrid Artificial Bee Colony Algorithms And Application

Artificial bee colony(ABC)algorithm is a swarm intelligence optimization algorithm which simulates the forging behavior of honeybees.Because of its simple structure,easy implementation and good global optimization performance,ABC has attracted extensive attention from domestic and foreign scholars.However,the basic ABC algorithm has the defects such as slow convergence and poor local search ability.Therefore,based on the principle of complementary advantages,this thesis enhances the ABC's optimization performance by comprehensively using the differences and advantages of different swarm intelligence algorithms in a hybrid way.In this thesis,the core search operators of symbiotic search algorithm and fireworks algorithm are introduced in ABC,and two hybrid ABC algorithms are proposed to solve practical application problems.The main contents are as follows:1.To relieve the drawbacks of slow convergence and poor local search ability of ABC algorithm,mutualism search operator of symbiotic organsims search(SOS)algorithm is introduced,and hybrid ABC algorithm with symbiotic search strategy is proposed.The mutualism search operator has strong local search ability through the information exchange between individuals and the guidance of optimal individual.Therefore,the mutualism search operator is incorporated into employed bee search of ABC,which speeds up the bees search.The CEC2014 test function is used to test the performance of the hybrid ABC algorithm.Compared with the existing ABC algorithms and other intelligence optimization algorithms,experimental results show that the rationality and effectiveness of the hybrid ABC algorithm.2.To balance the global search and local search ability of ABC algorithm,the explosion search operator is introduced,and a hybrid ABC algorithm based on firework explosion is proposed.The algorithm mixes the ABC with explosion search operator in a serial way,which is to perform the explosion search operation after the bee search.The search range of the explosion search operator is controlled through the amplitude of the explosion.In the early stage,it searches the potential solution area in the entire search space;as the explosion amplitude decreases,it searches for high-quality solutions in the potential area in the later stage.Therefore,a general firework explosion ABC framework is designed.The framework is applied to the existing six ABC,and the optimization performance of these firework explosion ABC algorithms are tested on CEC2014 test function.The experimental results show that the framework improves the search performance of the existing ABC algorithms.3.The two hybrid ABC algorithms are applied to the economic dispatch(ED)problem of power system.Two ED problems with different characteristics are selected and the total cost of power generation is taken as the objective function.Case one has 15 generation units without valve point effect.Case two has 40 generation units and the valve point effect is considered,which makes the ED problem have more local optima.The two hybrid algorithms are applied to optimize the above two cases and compared with other optimization algorithms.The experimental results show that these two hybrid ABC algorithms have advantage in solving ED problems with different characteristics and the total power cost is relatively small.