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In this article we propose the use of fuzzy systems for dynamic adjustment of parameters in the galactic swarm optimization (GSO) method. This algorithm is inspired by the movement of stars, galaxies and superclusters of galaxies under the force of gravity. GSO uses various cycles of exploration and exploitation phases to achieve a trade-off between the exploration of new solutions and exploitation...
Interactive evolutionary computation systems can be used to evolve advertisement texts. Google AdWords was used as the interface that users can use to see the advertisement texts, and have a chance of being persuaded by the text into clicking them. Interactive evolutionary computation systems use humans to perform fitness evaluation in the evolutionary process, which can be applied on a genetic algorithm...
An improved methodology for parameter adaptation in GSA (Gravitational Search Algorithm) is presented in where we use a fuzzy system to control the abilities of GSA to perform a global and local search. The results show that with our methodology GSA can outperform the quality of the results when compared with the original method and some other GSA improvements.
In this paper we propose a new method for dynamic parameter adaptation in the bat algorithm (BA). BA is a metaheuristic algorithm inspired by the behavior of micro bats, which has been applied to different optimization problems obtaining good results. In this paper we propose dynamic parameter adaptation of the BA using Interval Type-2 fuzzy logic. Simulation results show that the proposed method...
In this article we use the Differential Evolution (DE) algorithm which using fuzzy logic has the mutation parameter (F) dynamic, this modification of the algorithm we call Fuzzy Differential Evolution algorithm (FDE), a comparison algorithm using type 1 fuzzy logic and interval type 2 fuzzy logic is performed by for a set of functions Benchmark.
In this paper we propose a new method based on an interval type-2 fuzzy logic system for dynamic parameter adaptation in the harmony search (HS) algorithm. The main contribution of this paper is an improvement of HS in its abilities to search in a global and local fashion, by dynamically changing some of its parameters using an interval type-2 fuzzy logic system. The fuzzy harmony search algorithm...
A hybrid system composed by a generalized Type-2 Fuzzy Logic System (GT2FLS) and a fuzzy Bee Colony Optimization (FBCO) algorithm for the dynamic adaptation in the alpha and beta parameters is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is the analysis of the approach with Generalized Type-2 Fuzzy...
The main goal of the paper is the use of fuzzy logic for dynamic parameter adaptation in the Grey Wolf Optimizer (GWO) algorithm. The proposed approach of a fuzzy GWO is compared with the traditional GWO algorithm with a set of benchmark functions. Simulation results show that there is a significant advantage of the proposed fuzzy GWO.
We describe in this paper the Bat Algorithm and a proposed enhancement using a fuzzy system to dynamically adapt its parameter. The original method is compared with the proposed method and also compared with the genetic algorithm, providing a more complete analysis of the effectiveness of the bat algorithm. Simulation results on a set of mathematical functions with the fuzzy bat algorithm outperform...
This paper develops a new fuzzy harmony search algorithm (FHS) for solving optimization problems. FHS employs a novel method using fuzzy logic for adaptation of the harmony memory accepting parameter that enhances the accuracy and convergence rate of the harmony search (HS) algorithm. In this paper the impacts of constant parameters on harmony search algorithm are discussed and a strategy for tuning...
The proposed method in this paper describes the enhancement of the Cuckoo Search (CS) Algorithm via Lévy flights using a fuzzy system to dynamically adapt its parameters. The original CS method is compared with the proposed method called Fuzzy Cuckoo Search (FCS) on a set of benchmark mathematical functions. In this case we consider a fuzzy system to dynamically change parameters during the execution...
We describe in this paper the Bat Algorithm and a proposed enhancement using a fuzzy system to dynamically adapt its parameter, original method is compared with the proposed method and also compared with genetic algorithm, providing a more complete analysis of the effectiveness of the bat algorithm. Simulation results on a set of mathematical functions with the fuzzy bat algorithm outperform the traditional...
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