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ERIC Number: EJ1415171
Record Type: Journal
Publication Date: 2024
Pages: 17
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1532-0545
Improving Mathematical Exposition of an Industrial-Scale Linear Program
Gus Greivel; Alexandra Newman; Maxwell Brown; Kelly Eurek
INFORMS Transactions on Education, v24 n2 p119-135 2024
Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation "best practices" and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector.
Institute for Operations Research and the Management Sciences (INFORMS). 5521 Research Park Drive Suite 200, Catonsville, Maryland 21228. Tel: 800-446-3676; Tel: 443-757-3500; Fax: 443-757-3515; e-mail: informs@informs.org; Web site: https://pubsonline.informs.org/journal/ited
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Renewable Energy Laboratory (DOE)
Authoring Institution: N/A
Grant or Contract Numbers: N/A