Artificial Intelligence Assisted Optimization Under Uncertainty for Robust Solutions

Inapakurthi, Ravi kiran and Mitra, Kishalay (2022) Artificial Intelligence Assisted Optimization Under Uncertainty for Robust Solutions. In: 26th International Conference on System Theory, Control and Computing, ICSTCC 2022, 19-21 October 2022, Sinaia.

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Abstract

Uncertainty in process conditions makes the optimal solution from the deterministic optimization case infeasible or suboptimal. This mandates a special treatment for process uncertainty. The advent of unsupervised machine learning technique like clustering can be used to address this problem. Data arising from process conditions is meager and, to perform robust optimization, it is necessary to have enough representation of the uncertain region. For this, the collected data from process conditions is clustered using Support Vector Clustering (SVC). The hyper-parameters of SVC play a crucial role in clustering exercise. To promote this, a novel algorithm for determining optimal SVC models, is proposed. The proposed algorithm is used to cluster the uncertain process data and once clustered, can be used to sample additional data points inside each cluster using the convex hull. The additionally sampled data points in each cluster increases the cluster representativeness. The proposed methodology is implemented on industrial grinding circuits for performing Optimization Under Uncertainty (OUU) for the worst-case scenario and tested against the budget-uncertainty set based OUU. © 2022 IEEE.

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IITH Creators:

IITH Creators	ORCiD
Mitra, Kishalay	http://orcid.org/0000-0001-5660-6878

Item Type:

Conference or Workshop Item (Paper)

Additional Information:

Authors acknowledge the financial support received by the project grant # ST/NSM/R&D_HPC_Applications/2021/23 received from the Department of Science and Technology, Government of India, towards the execution of this work.

Uncontrolled Keywords:

algorithms; Artificial intelligence; data-driven robust optimization; optimization under uncertainty; support vector clustering

Subjects:

Chemical Engineering

Divisions:

Department of Chemical Engineering

Depositing User:

Ms Palak Jain

Date Deposited:

22 May 2023 09:29

Last Modified:

22 May 2023 09:29