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  4. MTGWA: A Multithreaded Gray Wolf Algorithm with Strategies Based on Simulated Annealing and Genetic Algorithms
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MTGWA: A Multithreaded Gray Wolf Algorithm with Strategies Based on Simulated Annealing and Genetic Algorithms

Journal
Computer Science and Health Engineering in Health Services
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
ISSN
1867-8211
1867-822X
Date Issued
2021
Author(s)
Murillo-Suarez, Alfonso
García-Jacas, Cesar Raúl
Guerrero-Valadez, Juan Manuel
Type
Resource Types::text::book::book part
DOI
10.1007/978-3-030-69839-3_11
URL
https://scripta.up.edu.mx/handle/20.500.12552/4389
Abstract
In this paper, we present an improvement of the Gray Wolf algorithm (GWO) based on a multi-threaded implementation of the original algorithm. The paper demonstrates how to combine the solutions obtained in each of the threads to achieve a final solution closer to the absolute minimum or even equal to it. To properly combine the solutions of each of the threads of execution, we use strategies based on simulated annealing and genetic algorithms. Also, we show the results obtained for twenty-nine functions: unimodal, multimodal, fixed dimension and composite functions. Experiments show that our proposed improves the results of the original algorithm. © Springer Nature
Subjects

Nature-inspired algor...

Optimization

Multi-threaded execut...

Optimization techniqu...

Metaheuristics

Gray Wolf algorithm

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