A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
A Visualizable Test Problem Generator for Many-Objective Optimization (2022)


Fieldsend, J. E., Chugh, T., Allmendinger, R., & Miettinen, K. (2022). A Visualizable Test Problem Generator for Many-Objective Optimization. IEEE Transactions on Evolutionary Computation, 26(1), 1-11. https://doi.org/10.1109/TEVC.2021.3084119


JYU-tekijät tai -toimittajat


Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Fieldsend, Jonathan E.; Chugh, Tinkle; Allmendinger, Richard; Miettinen, Kaisa

Lehti tai sarja: IEEE Transactions on Evolutionary Computation

ISSN: 1089-778X

eISSN: 1941-0026

Julkaisuvuosi: 2022

Volyymi: 26

Lehden numero: 1

Artikkelin sivunumerot: 1-11

Kustantaja: Institute of Electrical and Electronics Engineers (IEEE)

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1109/TEVC.2021.3084119

Julkaisun avoin saatavuus: Ei avoin

Julkaisukanavan avoin saatavuus:

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/76011


Tiivistelmä

Visualizing the search behavior of a series of points or populations in their native domain is critical in understanding biases and attractors in an optimization process. Distancebased many-objective optimization test problems have been developed to facilitate visualization of search behavior in a two-dimensional design space with arbitrarily many objective functions. Previous works have proposed a few commonly seen problem characteristics into this problem framework, such as the definition of disconnected Pareto sets and dominance resistant regions of the design space. The authors’ previous work has advanced this research further by providing a problem generator to automatically create user-defined problem instances featuring any combination of these problem features as well as newly introduced ones, such as landscape discontinuities, varying objective ranges, and neutrality. This work makes a number of additional contributions including the proposal of an enhanced, open-source feature-rich problem generator that can create user-defined problem instances exhibiting a range of problem features – some of which are newly introduced here or form extensions of existing features. A comprehensive validation of the problem generator is also provided using popular multiobjective optimization algorithms, and some problem generator settings to create instances exhibiting different challenges for an optimizer are identified.


YSO-asiasanat: optimointi; monitavoiteoptimointi; visualisointi; benchmarking; ongelmanratkaisu; avoin lähdekoodi

Vapaat asiasanat: multi-objective test problems; evolutionary optimization; benchmarking; test suite; visualization


Liittyvät organisaatiot


OKM-raportointi: Kyllä

Alustava JUFO-taso: 3


Viimeisin päivitys 2022-02-02 klo 10:23