Yazdani, D, Branke, J, Omidvar, MN orcid.org/0000-0003-1944-4624 et al. (2 more authors) (2018) Changing or keeping solutions in dynamic optimization problems with switching costs. In: Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18. The Genetic and Evolutionary Computation Conference, 15-19 Jul 2018, Kyoto. ACM Press , pp. 1095-1102. ISBN 9781450356183
Abstract
Dynamic optimization problems (DOPs) are problems that change over time. However, most investigations in this domain are focused on tracking moving optima (TMO) without considering the cost of switching from one solution to another when the environment changes. Robust optimization over time (ROOT) tries to address this shortcoming by finding solutions which remain acceptable for several environments. However, ROOT methods change solutions only when they become unacceptable. Indeed, TMO and ROOT are two extreme cases in the sense that in the former, the switching cost is considered zero and in the latter, it is considered very large. In this paper, we propose a new semi ROOT algorithm based on a new approach to switching cost. This algorithm changes solutions when: 1) the current solution is not acceptable and 2) the current solution is still acceptable but algorithm has found a better solution and switching is preferable despite the cost. The main objective of the proposed algorithm is to maximize the performance based on the fitness of solutions and their switching cost. The experiments are done on modified moving peaks benchmark (mMPB) and the performance of the proposed algorithm alongside state-of-the-art ROOT and TMO methods is investigated.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2018 Association for Computing Machinery. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Accounting & Finance Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 31 Jan 2020 10:18 |
Last Modified: | 11 Mar 2020 09:26 |
Status: | Published |
Publisher: | ACM Press |
Identification Number: | 10.1145/3205455.3205484 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156233 |