Artificial neural network models for knowledge representation in chemical engineering

Multiobjective optimization involves the simultaneous optimization of more than one objective function. This is quite commonly encountered in Chemical Engineering. A considerable amount of research has been reported in this area over the last twenty years. These are reviewed in the present paper. The general background of this area is presented at the beginning, followed by a description of how the results can be described in terms of Pareto sets. We then present the several methods available for generating these optimal solutions. Applications of optimization in Chemical Engineering wherein multiple objectives are encountered, as well as special adaptations of the basic algorithms required to solve these problems, are then discussed. Some comments are also made on possible directions that future research may take in this area.

Applications of multiobjective optimization in Chemical Engineering

The synthesis of cost optimal heat exchanger networks. An industrial review of the state of the art

Synthesis of heat exchanger networks

Intelligent systems in process engineering : A review

Optimal synthesis of heat exchange systems Necessary conditions for minimum heat transfer area and their application to systems synthesis

Synthesis of optimal heat exchange systems—an approach by the optimal assingment problem in linear programming

Developpement de quatre systemes experts experimentaux: synthese de sequences de distillation; synthese de systemes de commande de la distillation; choix des procedes de production de gaz inerte; probleme lie a la synthese des diagrammes P et I

Shigenobu Kobayashi

Papers

Optimal synthesis of heat exchange systems Necessary conditions for minimum heat transfer area and their application to systems synthesis

Synthesis of optimal heat exchange systems—an approach by the optimal assingment problem in linear programming

Some expert system experiments in process engineering

Interactive solution to multiple criteria problems in chemical process design: An approach by pairwise comparison