On the runtime of randomized local search and simple evolutionary algorithms for dynamic makespan scheduling
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Date
2015
Authors
Neumann, F.
Witt, C.
Editors
Yang, Q.
Wooldridge, M.
Wooldridge, M.
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Conference paper
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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
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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.
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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.