An Improved Simulated Annealing Algorithm for Global Optimization Problems with Continuous Variables
一种改进的连续变量全局优化模拟退火算法

In this paper, an improved simulated annealing (SA) algorithm is developed to solve the global optimization problems with continuous variables. By introducing a method of adaptive conversion function, the determination of initial temperature, usually a difficult problem in SA has been solved and becomes independent to the practical problems solved. Combined with the success-failure method and the variable metric method, the conception of effective shift-increment is proposed to improve the method generating new solutions. On the basis of the newly defined relative precision, a termination criterion is proposed to make better balance between the computational efficiency and the solution accuracy, and then, enhance the efficiency and robustness of the SA algorithm. The numerical test examples are given to demonstrate the feasibility and high-efficiency of the improved SA algorithm proposed in the paper.