Examples of using Heuristic algorithm in English and their translations into Portuguese
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The method used is based on a heuristic algorithm.
This new heuristic algorithm has the constructive character, because in each iteration goes to search for a new solution to the problem.
It's a collection of neural nets and heuristic algorithms.
They may claim to use heuristic algorithms, but it may well be hokum.
Instead of partial algorithms, they consider so-called errorless heuristic algorithms.
Mathematical optimization, heuristic algorithms and simulation techniques.
This work proposes a decomposition approach solution using mixed integer linear programming(milp)combined with heuristic algorithms.
Good. This is the first of several heuristic algorithms I need you to run.
A heuristic algorithm for obtaining linear graph layouts of low bandwidth is the Cuthill-McKee algorithm. .
The second method is to use a heuristic algorithm to find viruses based on common behaviours.
Many research works in the literature employ similarity measures to detect synonymy andto build hierarchies of tags automatically by means of heuristic algorithms.
I used pattern-recognition software and a basic heuristic algorithm to track your known aliases.
In this work, an heuristic algorithm to find a better configuration of channel and transmission power for those access points in the network is proposed.
Given the complexity of the problem,this work proposes three heuristic algorithms, all them based on metaheuristic iterated greedy ig.
Two heuristic algorithms will be presented for generating solutions for pep: the heuristic of null price and the heuristic of competitor price.
In this master's dissertation is presented the development of a specialized heuristic algorithm for planning the expansion of distribution systems.
This paper proposes the use of a heuristic algorithm based on the behavior of insects, which contributes to the interpretation of m-n graphic on computational way.
The problem is computationally difficult(NP-hard); however,efficient heuristic algorithms converge quickly to a local optimum.
The proposed methodology uses a constructive heuristic algorithm based on sensitivity indices, in which the expansion decisions are relaxed and represented through the hyperbolic tangent function.
The power capacity of these lines was modified by varying the geometry of the bundles and the quantity of sub-conductors,using a new algorithm based on the heuristic algorithms theory.
This article proposes the analysis and application of heuristic algorithms for the reconfiguration of distribution systems in order to reduce power losses in these systems.
First uses a constructive heuristic algorithm that tries to work with parameters instead of working with variables, with the objective of reducing the convergence time to the research process trying not to impair the quality of the solution.
Considered np-hard, several works address the resolution of pem through heuristic algorithms due to the limitations of the exact algorithms to work with large instances.
Errorless heuristic algorithms are essentially the same as the algorithms with benign faults defined by Impagliazzo where polynomial time on average algorithms are characterized in terms of so-called benign algorithm schemes.
Another advantage of this algorithm is the technique used to find the final topology, the specialized heuristic algorithm uses destructive technique for finding the final topology, on which, for each iteration, one line that is present in the current system configuration, is removed.
In this work we proposes a specialized heuristic algorithm for optimal allocation of capacitor banks in radial distribution systems, whose goal is to minimize costs due to energy losses, subject to some operational restrictions of the electric distribution system.
In this context the hybrid algorithm developed and implemented in this work,takes advantage of reducing the convergence time of the constructive heuristic algorithm and the advantage of guarantee that the solution has the best quality, which are the solutions produced by algorithms type branch and bound.
There has also been extensive research on heuristic algorithms for solving maximum clique problems without worst-case runtime guarantees, based on methods including branch and bound, local search, greedy algorithms, and constraint programming.
Methods for solving this problem using linear mixed integer programming and heuristic algorithms of differential evolution(binary differential evolution and discretized differential evolution) are proposed using binary variables.
To accomplish this goal the following subjects were developed: a constructive heuristic algorithm, which has as primary task the allocation of capacitor banks in buses with the most high-demand for reactive power and also search for an initial solution to minimize energy losses costs and a meta-heuristic which uses variable neighborhood descend search, in which we implemented appropriate neighborhood structures for the allocation problem of capacitor banks in electric system buses.