Why Use Interactive Multi-Objective Optimization in Chemical Process Design?
Miettinen, K., & Hakanen, J. (2009). Why Use Interactive Multi-Objective Optimization in Chemical Process Design?. In G. P. Rangaiah (Ed.), Multi-Objective Optimization: Techniques and Applications in Chemical Engineering (pp. 153-188). World Scientific.
Editors
Date
2009Copyright
Copyright © 2009 by World Scientific Publishing. This is an electronic final draft version of an article whose final and definitive form has been published in Multi-Objective Optimization by World Scientific Publishing.
Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements on the optimization methods used. In this paper, we point out some shortcomings of some widely used basic methods of multi-objective optimization. As an alternative, we suggest using interactive approaches where the role of a decision maker or a designer is emphasized. Interactive multi-objective optimization has been shown to suit well for chemical process design problems because it takes the preferences of the decision maker into account in an iterative manner that enables a focused search for the best Pareto optimal solution, that is, the best compromise between the conflicting objectives. For this reason, only those solutions that are of interest to the decision maker need to be generated making this kind of an approach computationally efficient. Besides, the decision maker does not have to compare many solutions at a time which makes interactive approaches more usable from the cognitive point of view. Furthermore, during the interactive solution process the decision maker can learn about the interrelationships among the objectives. In addition to describing the general philosophy of interactive approaches, we discuss the possibilities of interactive multi-objective optimization in chemical process design and give some examples of interactive methods to illustrate the ideas. Finally, we demonstrate the usefulness of interactive approaches in chemical process design by summarizing some reported studies related to, for example, paper making and sugar industries. Let us emphasize that the approaches described are appropriate for problems with more than two objective functions.
...
Publisher
World ScientificISBN
978-981-283-651-9Parent publication ISBN
Is part of publication
Multi-Objective Optimization: Techniques and Applications in Chemical EngineeringKeywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/17164064
Metadata
Show full item recordCollections
Related items
Showing items with similar title or keywords.
-
Why Use Interactive Multi-Objective Optimization in Chemical Process Design?
Miettinen, Kaisa; Hakanen, Jussi (World Scientific, 2017)Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements ... -
Designing empirical experiments to compare interactive multiobjective optimization methods
Afsar, Bekir; Silvennoinen, Johanna; Misitano, Giovanni; Ruiz, Francisco; Ruiz, Ana B.; Miettinen, Kaisa (Palgrave Macmillan, 2022)Interactive multiobjective optimization methods operate iteratively so that a decision maker directs the solution process by providing preference information, and only solutions of interest are generated. These methods ... -
Interactive Nonlinear Multiobjective Optimization Methods
Miettinen, Kaisa; Hakanen, Jussi; Podkopaev, Dmitry (Springer Science+Business Media, 2016)An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory ... -
Interactive Multiobjective Robust Optimization with NIMBUS
Zhou-Kangas, Yue; Miettinen, Kaisa; Sindhya, Karthik (Springer, 2018)In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty ... -
DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization
Misitano, Giovanni; Saini, Bhupinder Singh; Afsar, Bekir; Shavazipour, Babooshka; Miettinen Kaisa (Institute of Electrical and Electronics Engineers (IEEE), 2021)Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the ...