A4 Artikkeli konferenssijulkaisussa
A New Paradigm in Interactive Evolutionary Multiobjective Optimization (2020)


Saini, Bhupinder Singh; Hakanen, Jussi; Miettinen, Kaisa (2020). A New Paradigm in Interactive Evolutionary Multiobjective Optimization. In Bäck, Thomas; Preuss, Mike; Deutz, André; Wang, Hao; Doerr, Carola; Emmerich, Michael; Trautmann, Heike (Eds.) PPSN 2020 : 16th International Conference on Parallel Problem Solving from Nature, Lecture Notes in Computer Science, 12270. Cham: Springer, 243-256. DOI: 10.1007/978-3-030-58115-2_17


JYU-tekijät tai -toimittajat


Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Saini, Bhupinder Singh; Hakanen, Jussi; Miettinen, Kaisa

Emojulkaisu: PPSN 2020 : 16th International Conference on Parallel Problem Solving from Nature

Emojulkaisun toimittajat: Bäck, Thomas; Preuss, Mike; Deutz, André; Wang, Hao; Doerr, Carola; Emmerich, Michael; Trautmann, Heike

Konferenssin paikka ja aika: Leiden, The Netherlands, 5.-9.9.2020

ISBN: 978-3-030-58114-5

eISBN: 978-3-030-58115-2

Lehti tai sarja: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Julkaisuvuosi: 2020

Sarjan numero: 12270

Artikkelin sivunumerot: 243-256

Kirjan kokonaissivumäärä: 717

Kustantaja: Springer

Kustannuspaikka: Cham

Julkaisumaa: Sveitsi

Julkaisun kieli: englanti

DOI: https://doi.org/10.1007/978-3-030-58115-2_17

Avoin saatavuus: Julkaisukanava ei ole avoin

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/71637


Tiivistelmä

Over the years, scalarization functions have been used to solve multiobjective optimization problems by converting them to one or more single objective optimization problem(s). This study proposes a novel idea of solving multiobjective optimization problems in an interactive manner by using multiple scalarization functions to map vectors in the objective space to a new, so-called preference incorporated space (PIS). In this way, the original problem is converted into a new multiobjective optimization problem with typically fewer objectives in the PIS. This mapping enables a modular incorporation of decision maker’s preferences to convert any evolutionary algorithm to an interactive one, where preference information is directing the solution process. Advantages of optimizing in this new space are discussed and the idea is demonstrated with two interactive evolutionary algorithms: IOPIS/RVEA and IOPIS/NSGA-III. According to the experiments conducted, the new algorithms provide solutions that are better in quality as compared to those of state-of-the-art evolutionary algorithms and their variants where preference information is incorporated in the original objective space. Furthermore, the promising results require fewer function evaluations.


YSO-asiasanat: optimointi; monitavoiteoptimointi; evoluutiolaskenta; algoritmit; päätöksentukijärjestelmät

Vapaat asiasanat: interactive methods; achievement scalarizing functions; evolutionary algorithms; preference information; decision maker


Liittyvät organisaatiot


Hankkeet, joissa julkaisu on tehty


OKM-raportointi: Kyllä

Alustava JUFO-taso: 1


Viimeisin päivitys 2020-07-09 klo 07:40