A Simple Yet Effective Approach to Robust Optimization over Time

Lukas ADAM; Xin YAO

doi:10.1109/SSCI44817.2019.9002697

A Simple Yet Effective Approach to Robust Optimization over Time

Lukas ADAM, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

4 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 language	English
Title of host publication	2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	680-688
Number of pages	9
ISBN (Print)	9781728124858
DOIs	https://doi.org/10.1109/SSCI44817.2019.9002697
Publication status	Published - Dec 2019
Externally published	Yes

Funding

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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10.1109/SSCI44817.2019.9002697

Cite this

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title = "A Simple Yet Effective Approach to Robust Optimization over Time",

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. {\textcopyright} 2019 IEEE.",

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AB - 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.

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KW - particle swarm optimization

KW - robust optimization

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KW - uniform sampling

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DO - 10.1109/SSCI44817.2019.9002697

M3 - Conference paper (refereed)

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BT - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

A Simple Yet Effective Approach to Robust Optimization over Time

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Keywords

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