Test functions for optimization

In applied mathematics, test functions, known as artificial landscapes, are useful to evaluate characteristics of optimization algorithms, such as… (More)
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Topic mentions per year

2004-2016
01220042016

Papers overview

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2017
2017
When designing or developing optimization algorithms, test functions are crucial to evaluate performance. Often, test functions… (More)
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2017
2017
This article discusses issues related to the application of the user interactivity in optimization process, aided by the method… (More)
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2016
2016
The theoretical studies of differential evolution algorithm (DE) have gradually attracted the attention of more and more… (More)
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2016
2016
This paper uses active learning to solve the problem of mining bounded-time signal temporal requirements of cyber-physical… (More)
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2015
2015
Content of this contribution is an issue of inertial sensors errors, specification of inertial measurement units and generating… (More)
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2015
2015
This paper deals with the comparison of selected optimisation methods (random search, hill climbing, tabu search, local search… (More)
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2015
2015
We propose a novel GPU variant for genetic algorithm that uses constant memory effectively to store and share the elite… (More)
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2014
2014
Artificial bee colony is a meta-heuristic optimization algorithm based on the behavior of honey bee swarm. These bees work… (More)
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2008
2008
With information overload a real problem, especially on the Internet, there has been much interest in developing effective and… (More)
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2004
2004
In this paper we perform two experiments. In the first experiment we analyze the convergence ability to using different base for… (More)
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