Optimal synthesis of distillation columns:: Integration of process simulators in a disjunctive programming environment

The optimal economic design of a distillation Column involves the selection of the number of trays, feed and side-streams locations and operating conditions. In this paper we present a superstructure based optimization algorithm that combines the capabilities of commercial process simulators - taking advantage of the specially tailored algorithms designed for distillation and property estimation implemented in these simulators- and generalized disjunctive programming (GDP). The algorithm iterates between two types Of sub-problems: an NLP sub-problem, in which the trays are divided in existing and non-existing (non-existing trays behave like simple bypasses without mass or heat exchange) and an especially suited master (MILP) problem. NLP sub-problems are solved connecting the process simulator with an NLP external solver. An example is also included showing promising results.