Abstract: Based on the review of recent development of evolutionary computation and the principle of free energy minimization of thermodynamics, a new thermodynamics evolutionary algorithm for solving Shubert function optimization problem was proposed. The numerical experiments were conducted to measure the performance of thermodynamics evolutionary algorithm. The results show that thermodynamics evolutionary algorithm is of potential to obtain global optimum or more accurate solutions than other evolutionary methods.

Key words: thermodynamics evolutionary algorithm, Shubert function optimization problem, convergence and diversity

摘要： 综合国内外演化计算研究现状，基于热力学中的自由能极小化原理, 设计了一个全新的热力学演化算法，并通过对于Shubert函数优化问题求解的数值试验，测试了热力学演化算法的优良性能，实验结果表明了热力学演化算法求出的解比一般演化算法求出的解更加接近于全局最优。

关键词: 热力学演化算法, Shubert函数优化问题, 收敛性和多样性