Runtime Analysis of Typical Decomposition Approaches in MOEA/D for Many-Objective Optimization Problems.

Huang Z, Zhou Y, Chen Z, Dang Q

DOI: 10.1162/evco_a_00364
Published: 2026 Jul 13
Container: Evolutionary computation
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1162/evco_a_00364,
  title = {Runtime Analysis of Typical Decomposition Approaches in MOEA/D for Many-Objective Optimization Problems.},
  author = {Huang Z and Zhou Y and Chen Z and Dang Q},
  year = {2026},
  journal = {Evolutionary computation},
  doi = {10.1162/evco_a_00364},
  url = {https://doi.org/10.1162/evco_a_00364}
}

RIS

TY  - JOUR
TI  - Runtime Analysis of Typical Decomposition Approaches in MOEA/D for Many-Objective Optimization Problems.
AU  - Huang Z
AU  - Zhou Y
AU  - Chen Z
AU  - Dang Q
PY  - 2026
JO  - Evolutionary computation
DO  - 10.1162/evco_a_00364
UR  - https://doi.org/10.1162/evco_a_00364
ER  -

APA

Z, H., Y, Z., Z, C., & Q, D. (2026). Runtime Analysis of Typical Decomposition Approaches in MOEA/D for Many-Objective Optimization Problems.. Evolutionary computation. https://doi.org/10.1162/evco_a_00364

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pubmed · retrieved 2026-09-25T02:08:36.685Z