基于模拟退火思想的改进人工蜂群算法

Improved Artificial Bee Colony Algorithm Based on Simulated Annealing

针对人工蜂群算法(ABC)容易陷入局部极值点、进化后期收敛慢和优化精度较差等缺点。把模拟退火技术(SA)引入到ABC算法中,提出了一种改进的优化算法。混合优化算法在各温度下依次进行ABC和SA搜索,是一种两层的串行结构。由于ABC提供了并行搜索结构,所以,混合优化算法使SA转化成并行SA算法。SA的概率突跳性保证了种群的多样性,从而防止ABC算法陷入局部极小。基于模拟退火的改进人工蜂群算法保持了ABC算法简单容易实现的特点,改善了算法的全局优化能力,便于收敛的同时也可以防止算法陷入局部最优解。

Aiming at the shortcomings of artificial bee colony algorithm(ABC) easy to fall into local extreme point, slow convergence in late evolution and poor optimization accuracy. Simulated annealing technology(SA) is introduced into the ABC algorithm, and an improved optimization algorithm is proposed. The hybrid optimization algorithm performs ABC and SA search in sequence at each temperature and is a two-layer serial structure. Since ABC provides a parallel search structure, a hybrid optimization algorithm transforms SA into a parallel SA algorithm. The probabilistic suddenness of SA ensures the diversity of the population, thus preventing the ABC algorithm from falling into a local minimum. The improved artificial bee colony algorithm based on simulated annealing maintains the characteristics of the ABC algorithm that is simple and easy to implement, improves the algorithm’s global optimization ability, facilitates convergence, and prevents the algorithm from falling into the local optimal solution.