一种改进的连续变量全局优化模拟退火算法

在连续变量的全局优化问题求解中,提出了一种改进的模拟退火算法.该算法提出了一种自适应的函数变换方法,解决了模拟退火算法中较难处理的初始温度问题,使初始温度与具体应用问题无关;结合成功-失败法和变尺度方法,提出了有效偏移量的概念,改进了解的产生方式;提出了一种以相对精度为基础的结束准则,较好地解决了计算效率和计算精度的平衡,提高了算法的效率和通用性.数值测试算例验证了本文的改进模拟退火算法的可行性和高效性.

An Improved Simulated Annealing Algorithm for Global Optimization Problems with Continuous Variables

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.