On the runtime of randomized local search and simple evolutionary algorithms for dynamic makespan scheduling

Files

RA_hdl_109197.pdf (307.58 KB)
  (Restricted Access)

Date

2015

Authors

Neumann, F.
Witt, C.

Editors

Yang, Q.
Wooldridge, M.

Advisors

Journal Title

Journal ISSN

Volume Title

Type:

Conference paper

Citation

IJCAI : proceedings of the conference / sponsored by the International Joint Conferences on Artificial Intelligence, 2015 / Yang, Q., Wooldridge, M. (ed./s), vol.2015-January, pp.3742-3748

Statement of Responsibility

Frank Neumann and Carsten Witt

Conference Name

24th International Joint Conference on Artificial Intelligence (IJCAI 2015) (25 Jul 2015 - 31 Jul 2015 : Buenos Aires, Argentina)

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. Our results show that randomized local search and a simple evolutionary algorithm are very effective in dynamically tracking changes made to the problem instance.

School/Discipline

Dissertation Note

Provenance

Description

Access Status

Rights

Copyright © 2015 International Joint Conferences on Artificial Intelligence All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.

License

Call number

Persistent link to this record