Algorithmic synthesis of an optimal separation network comprising separators of different classes

A novel class of separation-network synthesis (SNS) problems is examined, where the separators in the separation network can be affected by various separation methods subject to different constraints imposed on the product specifications. Such a class of SNS problems has been rapidly gaining importance for chemical processing in general and biochemical processing in particular. The available methods for SNS are not intended to address these problems; therefore, an efficient method is proposed here to amend this situation. The method composes algorithmically the necessary mathematical model of the super-structure on which the determination of an optimal separation network is based. The resultant mathematical model is linear, thus the proposed method renders it possible to generate the optimal solution without fail. The solution might serve as the lower bound for a separation network with a non-linear cost function. The uniqueness and efficacy of the proposed method are amply demonstrated by two examples of different complexities.