Multicriteria optimization (MCO) is used to parametrize molecular models of water. The set of the best possible compromises between different objectives, the Pareto set, is determined. Calculating Pareto sets for optimization problems involving molecular simulations is computationally expensive. Therefore, we use a novel, highly efficient method, which is based on the fact that numerical results from molecular simulations can be interpreted as dimensionless numbers. Hence, they carry information on an entire class of models in physical units. This approach was applied here for the MCO of water models of the “one-center Lennard-Jones + point charge” type, in which the objectives were the quality of the description of the vapor pressure, liquid density, and enthalpy of vaporization. The results were compared to models from the literature. Significant improvements were observed. The new optimization method for the development of molecular models is efficient, robust, and broadly applicable.

中文翻译：

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使用简化单位方法对水分子模型进行多准则优化。

多标准优化（MCO）用于参数化水的分子模型。确定了不同目标之间最好的折衷方案，即帕累托方案。计算涉及分子模拟的优化问题的帕累托集在计算上是昂贵的。因此，我们使用一种新颖，高效的方法，该方法基于以下事实：分子模拟的数值结果可以解释为无量纲数。因此，它们以物理单位携带有关整个模型类别的信息。此方法在此处用于“单中心Lennard-Jones +点电荷”类型的水模型的MCO，其目标是描述蒸汽压，液体密度和汽化焓的质量。将结果与文献中的模型进行比较。观察到明显的改善。用于开发分子模型的新的优化方法高效，稳健并且广泛适用。