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Scalable Computational Methods for Sequential, Science-Based Design of Experiments using Pyomo.DoE

Year: 2025

Type: conference-paper

Abstract: Presentation explaining the new advancements for optimal design of sequential experimental campaign. Scalable computation was achieved through decomposition strategies on models relevant to initiatives across the IDAES software and supporting research portfolio (e.g., PrOMMiS, CCSI2).

DOI: 10.2172/2566797

Authors: Daniel Laky, Alexander Dowling

Institution: University of Notre Dame

Language: English

Topic: Optimal Experimental Design Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W4410576012

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