Abstract

A method for solving the problems of chemical process design taking into account the incompleteness and inaccuracy of the initial information presented in the form of one-stage optimization problems with joint chance constraints is proposed. Joint chance constraints guarantee the required probability level of performance, unlike individual chance constraints, which provide only an estimate of the level of performance. However, the calculation of joint chance constraints is much more complicated than that of individual chance constraints. This work proposes a method for solving the problems of chemical process design with allowance for joint chance constraints, which eliminates the operation of the direct calculation of constraints. The method involves converting a stochastic programming problem into a sequence of deterministic nonlinear programming problems and can significantly reduce the time it takes to solve the problem. The effectiveness of the proposed approach is illustrated by model examples.

中文翻译：

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考虑联合机会约束的化学过程设计

摘要

提出了一种解决化学过程设计问题的方法，该方法考虑了存在联合机会约束的一阶段优化问题形式的初始信息的不完整性和准确性。联合机会约束保证了所需的绩效概率水平，与个人机会约束不同，后者仅提供绩效水平的估计。但是，联合机会约束的计算比单个机会约束的计算要复杂得多。这项工作提出了一种解决化学过程设计问题的方法，该方法考虑了联合机会约束，从而消除了直接计算约束的操作。该方法涉及将随机规划问题转换为一系列确定性非线性规划问题，并且可以大大减少解决该问题所花费的时间。模型示例说明了该方法的有效性。