SYNTHESIS AND OPTIMIZATION OF A NONIDEAL DISTILLATION SYSTEM USING A PARALLEL GENETIC ALGORITHM

The automated synthesis of separation sequences for nonideal mixtures has only recently been attempted. The need for rigorous physical prope rty estimation procedures along with the possibly complex recycle stru ctures leads to the specification of a nonlinear programming problem, one in which both the objective function and the feasibility region ar e nonconvex. This paper describes the use of a stochastic optimization procedure, genetic algorithms, for the optimization of a preselected sequence of distillation units for the separation of a three component azeotropic mixture. By fixing the structure in terms of the units des ired, the optimization problem is reduced to one of designing each of the relevant units, choosing the appropriate operating conditions, and finding the optimal heat exchange network. To tackle the high computa tional effort required, the implementation uses a distributed memory m ulticomputer in the form of a network of workstations.