Surrogate-Assisted NSGA-II Algorithm for Expensive Multiobjective Optimization

Author:

Yagoubi Mouadh1ORCID,Bederina Hiba2ORCID

Affiliation:

1. IRT SystemX, Palaiseau, France

2. FreeLance, Massy, France

Publisher

ACM

Reference13 articles.

1. jMetalPy: A Python framework for multi-objective optimization with metaheuristics

2. Julian Blank and Kalyanmoy Deb . 2022 . GPSAF: A Generalized Probabilistic Surrogate-Assisted Framework for Constrained Single-and Multi-objective Optimization. arXiv preprint arXiv:2204.04054 (2022). Julian Blank and Kalyanmoy Deb. 2022. GPSAF: A Generalized Probabilistic Surrogate-Assisted Framework for Constrained Single-and Multi-objective Optimization. arXiv preprint arXiv:2204.04054 (2022).

3. Kalyanmoy Deb . 2011. Multi-objective optimisation using evolutionary algorithms: an introduction . Springer . Kalyanmoy Deb. 2011. Multi-objective optimisation using evolutionary algorithms: an introduction. Springer.

4. Kalyanmoy Deb , Amrit Pratap , Sameer Agarwal , and TAMT Meyarivan . 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II . IEEE transactions on evolutionary computation 6, 2 ( 2002 ), 182--197. Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and TAMT Meyarivan. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation 6, 2 (2002), 182--197.

5. Yaochu Jin . 2005. A comprehensive survey of fitness approximation in evolutionary computation. Soft computing 9, 1 ( 2005 ), 3--12. Yaochu Jin. 2005. A comprehensive survey of fitness approximation in evolutionary computation. Soft computing 9, 1 (2005), 3--12.

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