自适应状态转移模拟退火算法及其应用

状态转移模拟退火算法(STASA)作为解决复杂优化问题的有效方法，其搜索效率依赖于搜索算子和参数值的选择，在一些高维复杂问题上出现效率低下的问题。提出一种自适应状态转移模拟退火算法(ASTSA),通过自适应算子和参数选择策略来提高算法的适用性和求解效率；借鉴群智能算法的均值更新方法对平移算子进行改进，增强算子的搜索特性。通过23个基准测试函数和8个工程设计问题进行实验验证并与其他算法对比，证明了ASTSA算法和改进策略的有效性。

Adaptive state transition simulated annealing algorithm and its application

State transition simulated annealing(STASA) algorithm has achieved outstanding results in solving complex optimization problems. However, its search efficiency depends on the selection of search operators and parameter values, resulting in low efficiency in some high-dimensional complex problems. This paper proposed an adaptive STASA(ASTSA) algorithm by introducing adaptive operators and parameter selection strategies to improve the applicability and efficiency of the algorithm. And it improved the translation operator by referring the mean update method of swarm intelligence algorithms to enhance the search characteristics of operator. This paper demonstrated the effectiveness of ASTSA and the improved strategy through experimental validation with 23 benchmark test functions and 8 engineering design problems, and compared with other algorithms.