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Start Over Descriptor "GENETIC algorithms" Topic algorithms Language portuguese
3 results on '"GENETIC algorithms"'

1. APLICAÇÃO DE UM ALGORITMO GENÉTICO PARA O PROBLEMA DO CARTEIRO CHINÊS EM UMA SITUAÇÃO REAL DE COBERTURA DE ARCOS.

Author

Konowalenko, Flavia, Benevides, Paula Francis, Costa, Deise Maria Bertholdi, Barboza, Angela Olandoski, and Nunes, Luiz Fernando

Subjects
*GENETIC algorithms, *ALGORITHMS, *STREETS, *INDUSTRIAL wastes, *CITIES & towns
Abstract

The Chinese Postman Problem is an optimization problem that aims to cover all the arcs of a graph, minimizing the total distance traveled. Can be applied to non-directed graphs (two-way streets), directed (one-way streets) or mixed (some two-way streets and other one-way). These arch for the route is done by algorithms that generate approximate solutions. In this work we used a genetic algorithm for the construction of routes that approximate the optimal solution. The main objective is to minimize the cost of the course of collection and transportation solid waste in the city of Irati (PR), Brazil. The application of the algorithm was performed in a downtown area. Were used formapping, real data courtesy of City Hall officials. With the help of the online application Google Earth, we obtained the geographical coordinates of the vertices of the graph associated with the problem. The results generated by the genetic algorithm were compared with the optimal solution obtained by LINGO ® 12.0 software. These results were satisfactory for this mall instance of problems analyzed. [ABSTRACT FROM AUTHOR]

Published
2012

2. Hybrid evolutionary algorithms applied in production sequencing in a food industry

Author

Pereira Junior, Geraldo, Sanches, Danilo Sipoli, Morandin Junior, Orides, and Bressan, Glaucia Maria

Subjects
Ciência da Computação, Algorítmos, Food industry and trade, Algorítmos genéticos, Alimentos - Indústria, Genetic algorithms, CIENCIAS EXATAS E DA TERRA [CNPQ], Algorithms
Abstract

Este trabalho descreve um estudo comparativo entre algumas abordagens de sequenciamento de produção para um caso real em uma indústria de alimentos da cidade de Marília, SP. Para este problema, caracterizado como Job-Shop Scheduling Problem (JSSP), foram utilizados dois tipos de algoritmos evolutivos: Algoritmos Genéticos e Evolução Diferencial. Com o objetivo de aumentar a eficiência no processo de busca, estes algoritmos foram adaptados com técnicas de busca local. Além disso, é proposta uma heurística de balanceamento de carga a fim de alcançar regiões promissoras no espaço de busca. Para validação das abordagens propostas foi utilizado um cenário real de uma indústria de alimentos. This paper describes a comparative study of some production-scheduling scenarios for a real case in a food company located in Marilia, SP. For this problem, well known Job-Shop Scheduling Problem (JSSP), it was used two types of evolutionary algorithms: Genetic Algorithm and Differential Evolution. In order to increase the efficiency during the search process, these two algorithms have been adapted with local search techniques. Furthermore, it was proposed a heuristic based on load balancing in order to achieve promising regions in the search space. Finally, the proposed approaches have been validated for a real scenario from a food company.

Published
2018

3. A new genetic algorithm based scheduling algorithm for the LTE Uplink

Author

Saulo Henrique da Mata, Guardieiro, Paulo Roberto, Borin, Juliana Freitag, Teixeira, Márcio Andrey, Silva, Éderson Rosa da, and Cunha, Marcio José da

Subjects
Mathematical optimization, Computer science, Long-Term Evolution (Telecomunicações), Scheduling, Genetic Algorithms, Engenharia elétrica, Scheduling (computing), LTE, ns-3, Index-terms, Telecommunications link, Genetic algorithm, ENGENHARIAS::ENGENHARIA ELETRICA [CNPQ], Algoritmos genéticos, Uplink, Algorithms
Abstract

Tese (Doutorado) Long Term Evolution has become the de facto technology for the 4G networks. It aims to deliver unprecedented data transmission rates and low latency for several types of applications and services. In this context, this thesis investigates the resource allocation in the LTE uplink. From the principle that resource allocation in the uplink is a complex optimization problem, the main contribution of this thesis is a novel scheduling algorithm based on Genetic Algorithms (GA). This algorithm introduces new operations of initialization, crossover, mutation and a QoS-aware fitness function. The algorithm is evaluated in a mixed traffic environment and its performance is compared with relevant algorithms from the literature. Simulations were carried out in ns-3 and the results show that the proposed algorithm is able to meet the Quality of Service (QoS) requirements of the applications, while presenting a satisfactory execution time.

Published
2017

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