Examples of using Optimization problem in English and their translations into Italian
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Optimization problems for functions of several variables.
Development of distributed methods for optimization problems with applications to cyber-physical networks.
Free and constrained optimization problems.
Convex optimization problems; local and global optima.
Differential calculus in one real variable. Optimization problems.
Applications to the study of the graph of a function and to optimization problems.
Pseudo-Boolean optimization can be used to solve many kinds of combinatorial optimization problems.
This type of EA is often used in optimization problems.
Optimization problems can be divided into two categories depending on whether the variables are continuous or discrete.
In some global optimization problems the analytical definition of the objective function is unknown and it is only
For LSQ optimization problems, the data files are read by the core code.
Acquire the ability to recognize optimization problems and develop mathematical models of decision-making problems. .
Enables users to solve shape optimization problems which do not use only stress-oriented objective functions.
Be able to rigorously set up and solve optimization problems with and without constraints.
one is interested in optimization problems for which the decision versions are NP-complete.
is a type of approximation algorithm for optimization problems most often, NP-hard optimization problems.
studies ant artificial systems that take inspiration from the collective behavior of real ants to solve combinatorial optimization problems.
The method of Lagrange multipliers is widely used to solve challenging constrained optimization problems.
failure mechanics, structural optimization problems and stability problems. .
Due to the connection between approximation algorithms and computational optimization problems, reductions which preserve approximation in some respect are for this subject preferred than the usual Turing and Karp reductions.