Examples of using Combinatorial optimization problem in English and their translations into Portuguese
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Combinatorial optimization problems are widely studied in the literature.
So this problem can be classified as a combinatorial optimization problem.
It attempts to solve ordering combinatorial optimization problems, the most well-known of which is the traveling salesman problem tsp.
Several real-world problems can be stated as a combinatorial optimization problem.
However, for ordering combinatorial optimization problems, order-based genetic algorithms are more adequate than those with binary representation.
An optimization problem with discrete variables is known as a combinatorial optimization problem.
The problem is approached as a combinatorial optimization problem and a formulation is proposed.
This most often requires many changes when you have to apply the same metaheuristic to various types of combinatorial optimization problems.
An NP-optimization problem(NPO)is a combinatorial optimization problem with the following additional conditions.
This problem has many applications in manufacturing industries andbelongs to the class of combinatorial optimization problems np-hard.
Mathematically, this is a combinatorial optimization problem that presents a large number of variables and constraints, which often hinders their solution.
This work presents an adaptation of the differential evolution(de)algorithm for the solution of combinatorial optimization problems.
In a combinatorial optimization problem, we are looking for an object such as an integer, permutation or graph from a finite(or possibly countable infinite) set.
NP optimization problem===An"NP-optimization problem"(NPO)is a combinatorial optimization problem with the following additional conditions.
The aco is a computational intelligence technique inspired by the behavior of ants in nature andis used to solve combinatorial optimization problems.
In this work, we propose a new combinatorial optimization problem involving strings called maximum similarity partitioning problem. .
Classic and quantum-inspired genetic algorithms based on binary representations have been previously used to solve combinatorial optimization problems.
This methodology can be seen as a combinatorial optimization problem, where the goal is to find candidate values to substitute the missing ones in order to reduce the bias imposed by this issue.
The scheduling process involves complex operational constraints for determining transfer and storage activities,being a combinatorial optimization problem difficult to solve.
A brkga searches the solution space of the combinatorial optimization problem indirectly, therefore, it is necessary to specify how solutions are encoded and decoded and how their corresponding fitness values are computed.
A program was developed in c language to study a method that transforms, by means of genetic algorithms(gas),the calculation of some eigenvalues of symmetric matrices in a combinatorial optimization problem.
In mathematics, the minimum k-cut, is a combinatorial optimization problem that requires finding a set of edges whose removal would partition the graph to at least k connected components.
Abstract Research over the last decade or more shows that integration of integer programming(IP) and constraint programming(CP)methods can yield substantial benefits in the solution of combinatorial optimization problems.
The qap is a classic combinatorial optimization problem, which aims to minimize the sum of distances between pairs of different locations, weighted by¿ows between facilities allocated in them.
The aim of this work is to find the best parameters for hybrid cultural algorithm and over genetic algorithm, with model of islands(multipopulation characteristic)applied to combinatorial optimization problem called¿multidimensional knapsack¿.
Cutting and Packing(C& P)problems are hard combinatorial optimization problems that arise in the context of several manufacturing and process industries or in their supply chains.
Many of the problems that arise in the daily life of companies andcould be optimized fall into the class of np-hard combinatorial optimization problems, among them, cutting and packing problems cpp.
To analyze this approach is proposed to solve a combinatorial optimization problem with many practical applications, the problem of location of map labels. in computational tests are used test problems from the literature.
This work brings as well an application for the corresponding problem in the modeling of an important problem in computational biology known as transriptome reonstrution and quantiation problem. we consider such modeling the first to deal withthe transcriptome reconstruction and quantication problem as a combinatorial optimization problem involving strings.
The project design consists of a large combinatorial optimization problem, given a large number of possible configurations to be deployed, which was solved by a methodology based on genetic algorithm ga.