OptimizationClassesCert
plain-language theorem explainer
A structure certifies that the optimization problem classes have exactly five members. Researchers in operations research within Recognition Science cite it to confirm the match with configDim equal to five. The definition is realized as a structure with a single field for the finite type cardinality.
Claim. A structure asserting that the cardinality of the finite type of optimization classes is five, where the classes are the linear, convex nonlinear, integer, stochastic, and dynamic problems.
background
The module introduces five canonical optimization classes tied to the configuration dimension parameter set to five. These classes are linear, convex nonlinear, integer, stochastic, and dynamic. The referenced inductive definition provides the enumeration of these classes and derives the finite type instance used in the cardinality assertion. This establishes the local theoretical setting for classifying optimization problems in the framework.
proof idea
As a structure definition, it consists of a single field. The field directly states that the cardinality of the finite type instance for the optimization classes equals five, using the derived Fintype from the inductive enumeration.
why it matters
This supports the explicit certificate construction in the same module. It implements the claim of five optimization classes for configDim D equals five from the module documentation. Within Recognition Science, it relates to the dimension parameter but does not connect directly to the forcing chain or constants such as phi.
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