摘要： 在分析万有引力定律、牛顿第二定律的基础上,结合物体位移与加速度间的关系,给出一个位移与时间的相关函数,基于该函数提出一种启发式优化算法——引力移动算法。该算法中每个个体的初始位置在解空间中可随机选择,在优化阶段每个个体根据关联函数迭代更新各自的位置。随着迭代的进行,所有个体向每次迭代中取得最优解位置的个体逼近,直到所有个体收敛于全局最优解。使用13种基准函数进行实验,结果表明,该算法求解精度高于粒子群优化算法,具有较好的稳定性。
关键词:
引力移动算法,
启发式优化算法,
万有引力定律,
牛顿第二定律,
基准函数
Abstract: Based on the analysis of law of gravity and Newton’s second law,considering the relationship between displacement and acceleration,a new displacement-time function is conducted.Based on the function,a novel heuristic optimization algorithm named Gravitation Move Algorithm(GMA) is proposed.In this algorithm,search agents are distributed randomly in the search space.In each search phase,each search agent moves according to the proposed displacement-time function.Along with the iterations,all agents move forward to the best solution location achieved,until all agents converge to the global best solution.Experimental results show that GMA has better performance than PSO in solving various benchmark functions and it is stable.
Key words:
Gravitation Move Algorithm(GMA),
heuristic optimization algorithm,
law of gravity,
Newton’s second law,
benchmark function
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