A Simple Yet Effective Approach to Robust Optimization over Time

Lukas ADAM, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

2 Citations (Scopus)

Abstract

Robust optimization over time (ROOT) refers to an optimization problem where its performance is evaluated over a period of future time. Most of the existing algorithms use particle swarm optimization combined with another method which predicts future solutions to the optimization problem. We argue that this approach may perform subpar and suggest instead a method based on a random sampling of the search space. We prove its theoretical guarantees and show that it significantly outperforms the state-of-the-art methods for ROOT. © 2019 IEEE.
Original languageEnglish
Title of host publication2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages680-688
Number of pages9
ISBN (Print)9781728124858
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes

Bibliographical note

This work was supported by National Natural Science Foundation of China (Grant No. 61850410534), the Program for Guangdong Introducing Innovative and Enterpreneurial Teams (Grant No. 2017ZT07X386), Shenzhen Peacock Plan (Grant No. KQTD2016112514355531), and the Program for University Key Laboratory of Guangdong Province (Grant No. 2017KSYS008).

Keywords

  • dynamic optimization
  • particle swarm optimization
  • robust optimization
  • robust optimization over time
  • uniform sampling

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