Examples of using Optimization problems in English and their translations into Portuguese
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Solve a range of optimization problems.
Optimization problems, promise problems, etc.
Management science, optimization problems, mathematical modeling.
We will demonstrate how to incorporate uncertainty into optimization problems.
Combinatorial optimization problems are widely studied in the literature.
This work is dedicated to the study of two np-hard optimization problems.
Optimization problems can be represented by their search relations.
It forms the basis for the definition of the class MaxSNP of optimization problems.
Notation==Optimization problems are often expressed with special notation.
There is no corresponding constrained optimization problems for this one variable case.
For LSQ optimization problems, the data files are read by the core code.
The metaheuristics have an important role in solving various optimization problems.
Algorithms for optimization problems in discrete computational geometry, AV. EXT.
This system uses the metaphor of artificial life applied to solve optimization problems.
First, the method was tested for multiobjective optimization problems with continuous and integer variables.
The software development process involves activities that may be modeled as optimization problems.
Optimization problems can be divided into two categories depending on whether the variables are continuous or discrete.
Other types of problems include search problems and optimization problems.
In higher mathematics courses, optimization problems are usually solved with the use of differential calculus.
A meta-heuristic that has proven to be efficient in solving np-hard optimization problems are genetic algorithms ga.
The solution of linear optimization problems through interior point methods involves the solution of linear systems.
The reservoir engineering presents daily activities involved with optimization problems in different contexts.
Linear programming problems are optimization problems in which the objective function and the constraints are all linear.
However, complexity classes can be defined based on function problems, counting problems, optimization problems, promise problems, etc.
Optimization problems which have two or more global optimal solutions are known as global multimodal problems. .
A number of algorithms for other types of optimization problems work by solving LP problems as sub-problems.
Optimization problems with more than one objective consist in a topic very attractive for researchers due to its applicability in real-world situations.
A computational framework is developed in matlab for solving topology optimization problems using unstructured polygonal meshes in arbitrary two-dimensional domains.
The network optimization problems(nop) are common to several areas such as engineering, transport and telecommunications, and have been objects of intense research and studies.
PTAS reductions are used to define completeness in APX,the class of optimization problems with constant-factor approximation algorithms.