Chemical Process Design Taking into Account Joint Chance Constraints

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.