 On choosing the resolution of normative modelsJames H. Merrick and John P. Weyant European Journal of Operational Research, 2019, vol. 279, issue 2, 511-523 Abstract: Long time horizon normative models are frequently used for policy analysis, strategic planning, and system analysis. Choosing the granularity of the temporal or spatial resolution of such models is an important modeling decision, often having a first order impact on model results. This type of decision is frequently made by modeler judgment, particularly when the predictive power of alternative choices cannot be tested. In this paper, we show how the implicit tradeoffs modelers make in these formulation decisions, in particular in the tradeoff between the accuracy of representation enabled by the available data and model parsimony, may be addressed with established information theoretic ideas. The paper provides guidance for modelers making these tradeoffs or, in certain cases, enables explicit tests for assessing appropriate levels of resolution. We will mainly focus on optimization based normative models in the discussion here, and draw our examples from the energy and climate domain. Keywords: Problem structuring; Validation of OR computations; Information theory; Strategic planning; OR in environment and climate change (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:279:y:2019:i:2:p:511-523 DOI: 10.1016/j.ejor.2019.06.017 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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