Batch distillation processes, as most batch processes, are highly complex in nature and involve a number of operational and economical objectives that need to be considered. The performance of these processes depends on a number of different criteria that are often conflicting. An effective optimisation of such systems therefore requires the consideration of multi-criteria approaches to accommodate for the multi-objective nature of the problem and to effectively evaluate and optimise the performance in order to explore and understand the trade-offs between the multiple objectives (e.g. through the generation of a Pareto set).
Dedieu et al. (2003) considered the multi-objective design and retrofit of batch plants using a multi-objective genetic algorithm (MOGA). Their MOGA consisted of a combination of a single objective genetic algorithm and a Pareto sort procedure to optimise investment costs whilst at the same time minimising equipment sizing. Silva and Biscaia (2003) considered a constrained optimisation through a fuzzy penalty function of batch polymerisation reactors using a MOGA. They considered the maximisation of monomer conversion rate while minimising the concentration of initiator residue in the polymerisation reactor product.
This paper considers the simultaneous multi-objective optimisation of design and operation of hybrid batch distillation/pervaporation processes. The overall problem is formulated as a multi-objective mixed integer dynamic optimisation (MO-MIDO) problem. The multiple objectives include economic indices that reflect equipments capital investment, operating costs and production revenues. Several case studies for the separation of homogeneous binary mixtures are presented for a dual-criteria optimisation case in which the trade-offs between production and investment costs are explored. It is found that the genetic algorithm based multi-objective optimisation method is robust and able to adequately handle the multi-objective nature of the simultaneous design and operation of batch distillation columns.
1. Dedieu, S., L. Pibouleau, C. Azzaro-Pantel and S. Domenech, Design and retrofit of multiobjective batch plants via a multicriteria genetic algorithm, Computers & Chemical Engineering, 27(12), 1723-1740, 2003.
2. Silva, C. and E. Biscaia, Jr, Genetic algorithm development for multi-objective optimization of batch free-radical polymerization reactors, Computers & Chemical Engineering, 27(8-9), 1329-1344, 2003.