Multi-criteria optimization in chemical process design and decision support by navigation on Pareto sets

Abstract Designing chemical processes is a multi-criteria optimization problem with conflicting objectives. It can efficiently be solved using Pareto sets. These sets contain all solutions for which an improvement in any objective can only be achieved by accepting a decline in at least one other objective. This work integrates a novel algorithm to determine Pareto sets in a state-of-the-art steady-state flow sheet simulator. An approximation of predefined accuracy of the Pareto set, which can be convex or non-convex, is calculated. The decision maker can then navigate interactively on the Pareto set and explore the different optimal solutions. His decision is, hence, embedded in the knowledge of the entire Pareto set. The application of the method is illustrated by an example in which a distillation process for the separation of an azeotropic mixture (acetone + chloroform) is designed. Two process variants are compared: a pressure-swing and an entrainer distillation.

[1]  Jared L. Cohon,et al.  Multiobjective programming and planning , 2004 .

[2]  Geoffrey Basil Leyland,et al.  Multi-objective optimisation applied to industrial energy problems , 2002 .

[3]  Claudia Gutiérrez-Antonio,et al.  Pareto front of ideal Petlyuk sequences using a multiobjective genetic algorithm with constraints , 2009, Comput. Chem. Eng..

[4]  Philip Lutze,et al.  Design of hybrid distillation/melt crystallisation processes for separation of close boiling mixtures , 2013 .

[5]  Juha Hakala,et al.  An integrated multiobjective design tool for process design , 2006 .

[6]  J. Prausnitz,et al.  LOCAL COMPOSITIONS IN THERMODYNAMIC EXCESS FUNCTIONS FOR LIQUID MIXTURES , 1968 .

[7]  Johan Andersson,et al.  A survey of multiobjective optimization in engineering design , 2001 .

[8]  Andreas A. Linninger,et al.  Plant-Wide Waste Management. 1. Synthesis and Multiobjective Design , 2002 .

[9]  Y. Lim,et al.  Multiobjective Optimization in Terms of Economics and Potential Environment Impact for Process Design and Analysis in a Chemical Process Simulator , 1999 .

[10]  Günter Wozny,et al.  A Modular Approach to Sustainability Assessment and Decision Support in Chemical Process Design , 2010 .

[11]  A. M. Geoffrion.  Proper efficiency and the theory of vector maximization , 1968 .

[12]  Perry A. Appino,et al.  Approximating the noninferior set in multiobjective linear programming problems , 1993 .

[13]  P. Serafini,et al.  Scalarizing vector optimization problems , 1984 .

[14]  Matthias Ehrgott,et al.  Multicriteria Optimization , 2005 .

[15]  Yacov Y. Haimes,et al.  Multiobjective Decision Making: Theory and Methodology , 1983 .

[16]  Fernando Alonso,et al.  Multicriteria Optimization in Intensity Modulated Rediotherapy Planning , 2009 .

[17]  Adisa Azapagic,et al.  A Methodology for Integrating Sustainability Considerations into Process Design , 2006 .

[18]  Ajay K. Ray,et al.  APPLICATIONS OF MULTIOBJECTIVE OPTIMIZATION IN CHEMICAL ENGINEERING , 2000 .

[19]  Efstratios N. Pistikopoulos,et al.  Environmental impact minimization through material substitution: a multi-objective optimization approach , 2004 .

[20]  Kathrin Klamroth,et al.  Unbiased approximation in multicriteria optimization , 2003, Math. Methods Oper. Res..

[21]  Yacov Y. Haimes,et al.  Hierarchical analyses of water resources systems : modeling and optimization of large-scale systems , 1977 .