Optimization Meaning in a Sentence Through carefuloptimization, the software now runs much faster. 12 Theoptimizationof the website led to a significant increase in traffic. 8 Engineers are focused on theoptimizationof the engine's fuel efficiency. ...
The meaning of OPTIMIZATION is an act, process, or methodology of making something (such as a design, system, or decision) as fully perfect, functional, or effective as possible; specifically : the mathematical procedures (such as finding the maximum of
Optimizationstarted its gradual perfection in mid-19th-century English, when it was derived from optimize, a word first used in the early part of that same century with the meaning "to make the best or most of." In basic applications, optimization refers to the act or process of making som...
The breakthrough observation that made SMART a success was that programming an algorithm to search for English syntax was harder—and less useful—than programming it to simply search for semantics (that is, the words in the documents being searched are important, but not their lingual ...
Using the Marshal.SizeOf method instead of the sizeof operator will result in different values for some of these types, including bool and char, since Marshal.SizeOf computes the unmanaged size of a marshaled type, and these types are non-blittable (meaning that they may ...
(5) OSC projects are dynamic in nature, meaning that optimized decisions made in the early planning stage might be infeasible in later construction stages due to inevitable uncertainties [32]. Therefore, there is a need to make near-optimum planning decisions in a reasonable computation time. ...
Because c(x) is close to 0, the constraint is active, meaning it affects the solution. Recall the unconstrained solution. Get uncx uncx = 2×1 -0.6691 0.0000 Recall the unconstrained objective function. Get uncf uncf = -0.4052 See how much the constraint moved the solution and increas...
TolFunis a lower bound on the change in the value of the objective function during a step. If|f(xi) –f(xi+1)|<TolFun, the iterations end. Solvers generally useTolFunas arelativebound, meaning iterations end when|f(xi) –f(xi+1)|<TolFun(1 + |f(xi)|), or a similar relative...
The selection process for most optimizers implemented in apricot is greedy, meaning that one example is selected at a time and this is (usually) the best example to include next given those that have already been selected. While a greedy algorithm is not guaranteed to find the best subset of...
opts = optimoptions('fmincon','Algorithm','sqp') optimoptions“hides” some options, meaning it does not display their values. Those options do not appear in this table. Instead, they appear inHidden Options. Optimization Options