Valueknown

Valueknown is a term used in decision analysis, optimization, and modeling to denote a variable or parameter whose numerical value is known with certainty. It contrasts with parameters that are uncertain, estimated, or described by a probability distribution. In models, marking a parameter as valueknown signals that its value is fixed for the purposes of analysis or computation.

In formal notation, a valueknown parameter is treated as a constant. If x is valueknown and equals 5, then constraints and objective functions can be simplified accordingly. In optimization and constraint programming, identifying valueknown elements can reduce complexity through precomputation and constant folding, potentially speeding up solvers.

In data-driven contexts, valueknown can apply to measurements that are exact, calibrations with no error, or inputs supplied by external systems that guarantee accuracy. In decision making under uncertainty, distinguishing valueknown parameters from uncertain ones helps structure scenarios, sensitivity analyses, and risk assessments.

The term is not standardized across disciplines, and its precise meaning can vary by domain. Some uses equate valueknown with absolute certainty, while others allow for negligible tolerances due to numerical precision. As a concept, valueknown complements related ideas such as known-unknowns, uncertain parameters, and deterministic versus stochastic modeling.