Heat engines are fundamental physical objects to develop the nonequilibrium thermodynamics. The thermodynamic performance of the heat engine is determined by the choice of cycle and time-dependence of parameters. Here, we propose a systematic numerical method to find a heat engine cycle to optimize some target functions. We apply the method to heat engines with slowly varying parameters and show that the method works well. Our numerical method is based on the genetic algorithm which is widely applied to various optimization problems.

中文翻译：

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一种寻找微观热机最优热力循环的数值方法

热机是发展非平衡热力学的基本物理对象。热机的热力学性能由循环的选择和参数的时间依赖性决定。在这里，我们提出了一种系统的数值方法来寻找热机循环来优化一些目标函数。我们将该方法应用于参数缓慢变化的热机，并表明该方法运行良好。我们的数值方法基于广泛应用于各种优化问题的遗传算法。