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The optimum is the best or most favorable condition, or the greatest amount or degree possible under specific sets of comparable circumstances. Optimum may also refer to: Optimum (cable brand), a digital cable service; Optimum Releasing, a film and DVD distribution company based in the UK
The term derives from the Latin optimum, meaning "best". To be optimistic, in the typical sense of the word, is to expect the best possible outcome from any given situation. [1] This is usually referred to in psychology as dispositional optimism. It reflects a belief that future conditions will work out for the best. [2]
The choice among "Pareto optimal" solutions to determine the "favorite solution" is delegated to the decision maker. In other words, defining the problem as multi-objective optimization signals that some information is missing: desirable objectives are given but combinations of them are not rated relative to each other.
A thesaurus (pl.: thesauri or thesauruses), sometimes called a synonym dictionary or dictionary of synonyms, is a reference work which arranges words by their meanings (or in simpler terms, a book where one can find different words with similar meanings to other words), [1] [2] sometimes as a hierarchy of broader and narrower terms, sometimes simply as lists of synonyms and antonyms.
The definition of local minimum point can also proceed similarly. In both the global and local cases, the concept of a strict extremum can be defined. For example, x ∗ is a strict global maximum point if for all x in X with x ≠ x ∗ , we have f ( x ∗ ) > f ( x ) , and x ∗ is a strict local maximum point if there exists some ε > 0 such ...
This is a list of Latin words with derivatives in English (and other modern languages).. Ancient orthography did not distinguish between i and j or between u and v. [1] Many modern works distinguish u from v but not i from j.
So, we require the aspiration level to be at or below the optimum payoff. We can then define the set of satisficing options S as all those options that yield at least A: s ∈ S if and only if A ≤ U(s). Clearly since A ≤ U *, it follows that O ⊆ S. That is, the set of optimum actions is a subset of the set of satisficing options.
The goal is then to find for some instance x an optimal solution, that is, a feasible solution y with (,) = {(, ′): ′ ()}. For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0 .