基于模拟退火的万有引力算法

针对标准万有引力算法的个体位置更新策略可能对个体造成破坏且算法局部搜索能力较弱问题提出了一种改进算法。该算法将模拟退火思想引入万有引力算法，采用基于 Metroplis 准则的个体位置更新策略，并在引力操作之后，对每代最优个体进行退火操作。一定程度避免了个体移动的盲目性，提高了算法的局部搜索能力、收敛速度与精度。实验结果表明:算法的改进策略是有效的，且改进后的算法在收敛速度、收敛精度等方面具有明显优势。

The Gravity Algorithm Based Simulated Annealing

In Gravitational Search Algorithm(GSA),individual location update strategy may damage the individual, and the local search ability is weak,an improved algorithm has been proposed. The proposed algorithm integrated simulated annealing mechanism into GSA,used individual location update strategy which based on Metroplis,and did annealing operation for optimal individual of every generation after gravity operation. To some extent,avoided the individual blind Mobile,Improve the local search ability of the algorithm,the velocity and precision of convergence. The experimental results demonstrate that improvement strategy of the algorithm is effective,and the improved algo-rithm has obvious advantages in the velocity of convergence,convergence accuracy,etc.