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.
Toimittajat
Päivämäärä
2009Tekijänoikeudet
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.
...
Julkaisija
World ScientificEmojulkaisun ISBN
978-981-283-651-9Kuuluu julkaisuun
Multi-Objective Optimization: Techniques and Applications in Chemical EngineeringAsiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/17164064
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Lisenssi
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
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 ... -
On solving computationally expensive multiobjective optimization problems with interactive methods
Ojalehto, Vesa (University of Jyväskylä, 2014) -
Approximation method for computationally expensive nonconvex multiobjective optimization problems
Haanpää, Tomi (University of Jyväskylä, 2012) -
A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution
Sindhya, Karthik; Ruuska, Sauli; Haanpää, Tomi; Miettinen, Kaisa (Springer, 2011)Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, ... -
Parametrien tunnistus ja datajoukon sovittaminen optimoinnin avulla Potku-ohjelmassa
Rekilä, Heta (2019)Tutkielmassa perehdytään erityyppisiin optimointialgoritmeihin, joita modeFRONTIER-optimointiympäristö tarjoaa. Ympäristöä voi käyttää tehokkaaseen optimointialgoritmien vertailuun. Algoritmien suoriutumisen arviointia ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.