2003Kongzhi yu jueceRequires access

Optimization algorithm using two kinds of chaos and its application

Yuhe Zhang

Open publisher page 2 citations

Abstract

In order to avoid blind searching before reducing the searching space of variable optimized in chaos optimization algorithm, an optimization algorithm using two kinds of chaos is proposed. The algorithm searches the searching space of variable optimized using two kinds of different chaos simultaneously, then reduces the searching space of variable optimized according to their searching results. The method can also improve the regularity of the algorithm and avoid choosing different parameters for different optimization function. The simulation results show that the efficiency of the algorithm is higher than that of usual ones.

About this research paper

What this paper is about

In order to avoid blind searching before reducing the searching space of variable optimized in chaos optimization algorithm, an optimization algorithm using two kinds of chaos is proposed. The algorithm searches the searching space of variable optimized using two kinds of different chaos simultaneously, then reduces the searching space of variable optimized according to their searching results. The method can also improve the regularity of the algorithm and avoid choosing different parameters for different optimization function. The simulation results show that the efficiency of the algorithm is higher than that of usual ones.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In order to avoid blind searching before reducing the searching space of variable optimized in chaos optimization algorithm, an optimization algorithm using two kinds of chaos is proposed. The algorithm searches the searching space of variable optimized using two kinds of different chaos simultaneously, then reduces the searching space of variable optimized according to their searching results. The method can also improve the regularity of the algorithm and avoid choosing different parameters for different optimization function. The simulation results show that the efficiency of the algorithm is higher than that of usual ones.

Key concepts: CHAOS (operating system), Variable (mathematics), Algorithm, Optimization algorithm, Mathematical optimization, Space (punctuation), Mathematics, Optimization problem

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