@inproceedings{ae0047dffe3449a7ba10eb538ca331f7,
title = "A Continuation Method Based on CMA-ES",
abstract = "In this poster, we showcase a new algorithm for approximating the Pareto set of two-objective (unconstrained) optimization problems based on the idea of continuation. The algorithm tries to move “along” the Pareto set from one single-objective optimum to the other and back via a single-objective reformulation of the two-objective problem and the well-known CMA-ES as single-objective solver. The introduced algorithm BOG-CMA-ES (standing for biobjective gradient based CMA-ES) is visually analyzed on simple convex-quadratic objective functions and extensively benchmarked on the bbob-biobj test suite of the COCO platform, including comparisons with current state-of-the-art algorithms.",
author = "Vu, \{Hoang Nguyen\} and Dimo Brockhoff",
note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 2025 Genetic and Evolutionary Computation Conference Companion, GECCO 2025 Companion ; Conference date: 14-07-2025 Through 18-07-2025",
year = "2025",
month = aug,
day = "11",
doi = "10.1145/3712255.3726645",
language = "English",
series = "GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",
pages = "439--442",
editor = "Gabriela Ochoa",
booktitle = "GECCO 2025 Companion - Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion",
}