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optimality's Usage Examples:

Like computational neuroscience and econometrics, mathematical psychology theory often uses statistical optimality as a guiding principle, assuming that the human brain has evolved to solve problems in an optimized way.

is a functional that is used to establish an optimality criterion for segmenting an image into sub-regions.

Building the tree from the bottom up guaranteed optimality, unlike the top-down approach of Shannon–Fano coding.

the orthogonality principle is a necessary and sufficient condition for the optimality of a Bayesian estimator.

search method needs to be modified to continue the search beyond local optimality; see for example iterated local search, tabu search, reactive search optimization.

an optimality model that usually describes the behavior of an optimally foraging individual in a system where resources (often food) are located in discrete.

optimality is a situation where no individual or preference criterion can be better off without making at least one individual or preference criterion worse off.

many fields of computer science due to its completeness, optimality, and optimal efficiency.

The most common optimality criterion used to select this parameter is the expected L2 risk function, also termed the mean integrated squared error:\operatorname{MISE} (h) \operatorname{E}\!\left[\, \int (\hat{f}_h(x) - f(x))^2 \, dx \right].

second-order conditions as well is sufficient to establish at least local optimality.

admissible heuristic can ensure optimality.

brute-force algorithm, and observes the non-optimality of the nearest neighbour heuristic: We denote by messenger problem (since in practice this question should.

Seeking optimality, it is a compromise between the competing merits and demerits of the Likert scale and the Analog scale.