Approximation-Guided Evolutionary Multi-Objective Optimization

Bringmann, Karl; Friedrich, Tobias; Neumann, Frank; Wagner, Markus

doi:10.5591/978-1-57735-516-8/IJCAI11-204

Approximation-Guided Evolutionary Multi-Objective Optimization

Karl Bringmann, Tobias Friedrich, Frank Neumann, Markus Wagner

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 1198-1202.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-204

Abstract

Multi-objective optimization problems arise frequently in applications but can often only be solved approximately by heuristic approaches. Evolutionary algorithms have been widely used to tackle multi-objective problems. These algorithms use different measures to ensure diversity in the objective space but are not guided by a formal notion of approximation. We present a new framework of an evolutionary algorithm for multi-objective optimization that allows to work with a formal notion of approximation. Our experimental results show that our approach outperforms state-of-the-art evolutionary algorithms in terms of the quality of the approximation that is obtained in particular for problems with many objectives.

Karl Bringmann, Tobias Friedrich, Frank Neumann, and Markus Wagner. 2011. Approximation-Guided Evolutionary Multi-Objective Optimization. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 1198–1202. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-204

@inproceedings{ijcai2011p204,
  title     = {Approximation-Guided Evolutionary Multi-Objective Optimization},
  author    = {Bringmann, Karl and Friedrich, Tobias and Neumann, Frank and Wagner, Markus},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {1198--1202},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-204},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-204},
}

TY  - CPAPER
TI  - Approximation-Guided Evolutionary Multi-Objective Optimization
AU  - Bringmann, Karl
AU  - Friedrich, Tobias
AU  - Neumann, Frank
AU  - Wagner, Markus
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 1198
EP  - 1202
DO  - 10.5591/978-1-57735-516-8/IJCAI11-204
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-204
ER  -