中文摘要：

作为计算智能关键技术的演化计算,因其在对复杂和非线性问题的求解中表现出良好的适应性、并行性、鲁棒性等众多优点,受到众多领域专家学者的广泛关注。在综合国内外演化计算研究现状的基础上,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,并通过对于六峰值驼背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,试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。

英文摘要：

As a key technique of computational intelligence, evolutionary computation has attracted increasing interest because of its advantages of self-adaptation, parallelism, and robustness in solving complex and nonlinear problems. 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 six-hump camel back function optimization problem is proposed. Numerical experiments are 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.