Surrogate-based optimization of a periodic rescheduling algorithm
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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16
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AIChE Journal, Volume 68, issue 6
Abstract
Periodic rescheduling is an iterative method for real-time decision-making on industrial process operations. The design of such methods involves high-level when-to-schedule and how-to-schedule decisions, the optimal choices of which depend on the operating environment. The evaluation of the choices typically requires computationally costly simulation of the process, which—if not sufficiently efficient—may result in a failure to deploy the system in practice. We propose the continuous control parameter choices, such as the re-optimization frequency and horizon length, to be determined using surrogate-based optimization. We demonstrate the method on real-time rebalancing of a bike sharing system. Our results on three test cases indicate that the method is useful in reducing the computational cost of optimizing an online algorithm in comparison to the full factorial sampling.Description
Publisher Copyright: © 2022 The Authors. AIChE Journal published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.
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Citation
Ikonen, T, Heljanko, K & Harjunkoski, I 2022, 'Surrogate-based optimization of a periodic rescheduling algorithm', AIChE Journal, vol. 68, no. 6, e17656. https://doi.org/10.1002/aic.17656