On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling
Abstract
Evolutionary algorithms have been frequently used for dynamic optimization problems. With this paper, we contribute to the theoretical understanding of this research area. We present the first computational complexity analysis of evolutionary algorithms for a dynamic variant of a classical combinatorial optimization problem, namely makespan scheduling. We study the model of a strong adversary which is allowed to change one job at regular intervals. Furthermore, we investigate the setting of random changes.
Cite
Text
Neumann and Witt. "On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Neumann and Witt. "On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/neumann2015ijcai-runtime/)BibTeX
@inproceedings{neumann2015ijcai-runtime,
title = {{On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling}},
author = {Neumann, Frank and Witt, Carsten},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {3742-3748},
url = {https://mlanthology.org/ijcai/2015/neumann2015ijcai-runtime/}
}