Примери коришћења Optimization problem на Енглеском и њихови преводи на Српски
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Pose the optimization problem.
We can put this together to get the optimization problem.
Solve the optimization problem.
The traveling salesman problem is what is called a conventional optimization problem.
Solving the optimization problem.
An optimization problem asks for finding a"best possible" solution among the set of all possible solutions to a search problem. .
Solving of the optimization problem.
Set an optimization problem and optimize a system using software.; 4.
Solution of the optimization problem.
Reactive search optimization(RSO)advocates the integration of sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems.
Formulation of the optimization problem.
For specific optimization problems and problem instances, other optimization algorithms may be more efficient than genetic algorithms in terms of speed of convergence.
Word wrapping is an optimization problem.
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{\displaystyle m_{0}}.
Formal definition of an optimization problem.
Such a formulation is called an optimization problem or a mathematical programming problem(a term not directly related to computer programming, but still in use for example in linear programming- see History below).
But that's still just an optimization problem.
Unlike other deep architectures, such as DBNs, the goal is not to discover the transformed feature representation. The structure of the hierarchy of this kind of architecture makes parallel learning straightforward,as a batch-mode optimization problem.
Regularization can be added to this optimization problem by instead maximizing[5].
Further extending this example, it is possible to fix one joint and analytically solve for the other joints, but perhaps a better solution is offered by numerical methods(next section),which can instead optimize a solution given additional preferences(costs in an optimization problem).
Corresponding to the constraint optimization problem one can form the Lagrangian function.
However, complexity classes can be defined based on function problems(an example is FP),counting problems(e.g. P), optimization problems, promise problems, etc.
Matrix chain multiplication- is an optimization problem that can be solved using dynamic programming.
Results about NP-hardness in theoretical computer science make heuristics the only viable option for a variety of complex optimization problems that need to be routinely solved in real-world applications.
In mathematics and computer science, an optimization problem is the problem of finding the best solution from all feasible solutions.
In collaboration with Shen Lin he devised well-known heuristics for two NP-complete optimization problems: graph partitioning and the travelling salesman problem. .
Blend optimization is a nonlinear combinatorial optimization problem where the objective is typically to maximize revenue, Net Present Value(NPV), or monthly product tonnage targets.[2] Important features of the blending problem include.
The method of Lagrange multipliers can be used to reduce optimization problems with constraints to an unconstrained optimization problems.
Suppose we have two optimization problems such that instances of one problem can be mapped onto instances of the other, in a way that nearly optimal solutions to instances of the latter problem can be transformed back to yield nearly optimal solutions to the former.
Other variants, like genetic algorithms for online optimization problems, introduce time-dependence or noise in the fitness function.