DOI:
https://doi.org/10.14483/22484728.14625Publicado:
2017-10-27Número:
Vol. 11 Núm. 2 (2017)Sección:
Visión InvestigadoraGenetic algorithms for optimization and study transport tours
Algoritmos genéticos para optimización y estudio de viajes en transporte
Palabras clave:
Genetic algorithm, genetic operators, route optimization, traveling salesman (en).Palabras clave:
algoritmo genético, operadores genéticos, optimización de ruta, vendedor ambulante. (es).Descargas
Resumen (en)
This paper is the result of a research project developed by the DIGITI’s research group at Francisco José de Caldas University, on optimization problems by using artificial intelligence and it shows the implementation of a genetic algorithm (GA) as a tool for planning and optimization transport tours, with the goal of finding the best path destinations for a fleet of vehicles. It presents basic concepts of the theory and the results obtained, about the administration and logistics in the supply chain, through a planning solution that optimizes the use of transportation resources.
Resumen (es)
Este artículo es el resultado de un proyecto de investigación desarrollado por el grupo de investigación de DIGITI en la Universidad Distrital Francisco José de Caldas sobre problemas de optimización con inteligencia artificial; muestra la implementación de un algoritmo genético como herramienta de planificación y optimización de viajes en transporte, con el objetivo de encontrar la mejor ruta de destinos para una flota de vehículos. Presenta los conceptos básicos de la teoría y los resultados obtenidos, sobre la administración y logística en la cadena de suministro, a través de una solución de planificación que optimiza el uso de los recursos de transporte
Referencias
[1] H. Ronald, “Logistics Management Supply Chain”. Fifth Edition, Mexico: Pearson Education, 2004, p 14 and 64.
[2] M. Held and R. M. Karp, "A dynamic programming approach to sequencing problems," Journal of the Society for Industrial and Applied Mathematics, issue 10,1962, pp. 196-210
[3] R. Bellman and S. Dreyfus, “Applied Dynamic Programming”. Princeton University Press, 1962. https://doi.org/10.1515/9781400874651
[4] Winston, “Operations Research W.L. Applications and Algorithms”. Editorial Latin America, 1994.
[5] M.M. Flood, “The traveling salesman problem”, Operations Research, vol 4, no. 1, Feb. 1956. https://doi.org/10.1287/opre.4.1.61
[6] K. Menger, “Das Botenproblem,” Mathematische eines Ergibnisse Kolloquims 2 Teubner, Leipzig, pp. 12-12, 1930.
[7] J. B. Robinson, "On the Hamiltonian game (a traveling-salesman problem)", RAND Research Memorandum RM-303. 1949.
[8] G. Dantzig, R. Fulkerson, S. Johnson, “Solution of a Large-Scale Traveling-Salesman Problem” Journal of the Operations Research Society of America, vol 2, no. 4 p. 393-410, Nov, 1954. https://doi.org/10.1287/opre.2.4.393
[9] Donald Davendra and Yuan-bin Mo “The Advantage of Intelligent Algorithms for TSP”, Traveling Salesman Problem, Theory and Applications, Prof. Donald Davendra (Ed.), InTech, 2010, https://doi.org/10.5772/12897
[10] T. Murata, and H. Ishibuchi, “MOGA: Multi-objetive genetic algorithms”, Proceedings of the second IEEE International Conference on Evolutionary Computation 1, pp. 289-294, 1995. https://doi.org/10.1109/ICEC.1995.489161
[11] J.H Holland, “Adaptation in natural and artificial systems”, MIT Press, 1975.
[12] C. Darwin, “The origin of species by means of natural selection” New york: D. Appleton and Company, 1859.
[13] B. Chakraborty and P. Chaudhuri, "On the Use of Genetic Algorithm with Elitism in Robust and Nonparametric Multivariate Analysis", austrian journal of statistics, issue 32, pp. 13-27, 2003.
[14] D. E. Goldberg and K. Deb, “comparative analysis of selection schemes used in genetic algorithms”. In G. J. E. & Rawlins (Eds.), Foundations of genetic algorithms, Morgan Kaufmann Publishers, pp. 307-333, 1991. https://doi.org/10.1016/B978-0-08-050684-5.50008-2
[15] D. E. Goldberg and R. Lingle. “Alleles, loci, and the traveling salesman problem”. In Proceedings of the International Conference on Genetic Algorithms and Their Applications, pp.154-159, 1985.
[16] O. Abdoun, J. Abouchabaka and C. Tajani “Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem CoRR”, IJES International Journal of Emerging Sciences, vol 2, no 1, pp. 61-77, 2012.
[2] M. Held and R. M. Karp, "A dynamic programming approach to sequencing problems," Journal of the Society for Industrial and Applied Mathematics, issue 10,1962, pp. 196-210
[3] R. Bellman and S. Dreyfus, “Applied Dynamic Programming”. Princeton University Press, 1962. https://doi.org/10.1515/9781400874651
[4] Winston, “Operations Research W.L. Applications and Algorithms”. Editorial Latin America, 1994.
[5] M.M. Flood, “The traveling salesman problem”, Operations Research, vol 4, no. 1, Feb. 1956. https://doi.org/10.1287/opre.4.1.61
[6] K. Menger, “Das Botenproblem,” Mathematische eines Ergibnisse Kolloquims 2 Teubner, Leipzig, pp. 12-12, 1930.
[7] J. B. Robinson, "On the Hamiltonian game (a traveling-salesman problem)", RAND Research Memorandum RM-303. 1949.
[8] G. Dantzig, R. Fulkerson, S. Johnson, “Solution of a Large-Scale Traveling-Salesman Problem” Journal of the Operations Research Society of America, vol 2, no. 4 p. 393-410, Nov, 1954. https://doi.org/10.1287/opre.2.4.393
[9] Donald Davendra and Yuan-bin Mo “The Advantage of Intelligent Algorithms for TSP”, Traveling Salesman Problem, Theory and Applications, Prof. Donald Davendra (Ed.), InTech, 2010, https://doi.org/10.5772/12897
[10] T. Murata, and H. Ishibuchi, “MOGA: Multi-objetive genetic algorithms”, Proceedings of the second IEEE International Conference on Evolutionary Computation 1, pp. 289-294, 1995. https://doi.org/10.1109/ICEC.1995.489161
[11] J.H Holland, “Adaptation in natural and artificial systems”, MIT Press, 1975.
[12] C. Darwin, “The origin of species by means of natural selection” New york: D. Appleton and Company, 1859.
[13] B. Chakraborty and P. Chaudhuri, "On the Use of Genetic Algorithm with Elitism in Robust and Nonparametric Multivariate Analysis", austrian journal of statistics, issue 32, pp. 13-27, 2003.
[14] D. E. Goldberg and K. Deb, “comparative analysis of selection schemes used in genetic algorithms”. In G. J. E. & Rawlins (Eds.), Foundations of genetic algorithms, Morgan Kaufmann Publishers, pp. 307-333, 1991. https://doi.org/10.1016/B978-0-08-050684-5.50008-2
[15] D. E. Goldberg and R. Lingle. “Alleles, loci, and the traveling salesman problem”. In Proceedings of the International Conference on Genetic Algorithms and Their Applications, pp.154-159, 1985.
[16] O. Abdoun, J. Abouchabaka and C. Tajani “Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem CoRR”, IJES International Journal of Emerging Sciences, vol 2, no 1, pp. 61-77, 2012.
Cómo citar
APA
Parra Romero, M. C., Pantoja Benavides, J. F., y Giraldo Ramos, F. N. (2017). Genetic algorithms for optimization and study transport tours. Visión electrónica, 11(2), 161–168. https://doi.org/10.14483/22484728.14625
ACM
[1]
Parra Romero, M.C. et al. 2017. Genetic algorithms for optimization and study transport tours. Visión electrónica. 11, 2 (oct. 2017), 161–168. DOI:https://doi.org/10.14483/22484728.14625.
ACS
(1)
Parra Romero, M. C.; Pantoja Benavides, J. F.; Giraldo Ramos, F. N. Genetic algorithms for optimization and study transport tours. Vis. Electron. 2017, 11, 161-168.
ABNT
PARRA ROMERO, María Camila; PANTOJA BENAVIDES, Jaime Francisco; GIRALDO RAMOS, Frank Nixon. Genetic algorithms for optimization and study transport tours. Visión electrónica, [S. l.], v. 11, n. 2, p. 161–168, 2017. DOI: 10.14483/22484728.14625. Disponível em: https://revistas.udistrital.edu.co/index.php/visele/article/view/14625. Acesso em: 5 nov. 2024.
Chicago
Parra Romero, María Camila, Jaime Francisco Pantoja Benavides, y Frank Nixon Giraldo Ramos. 2017. «Genetic algorithms for optimization and study transport tours». Visión electrónica 11 (2):161-68. https://doi.org/10.14483/22484728.14625.
Harvard
Parra Romero, M. C., Pantoja Benavides, J. F. y Giraldo Ramos, F. N. (2017) «Genetic algorithms for optimization and study transport tours», Visión electrónica, 11(2), pp. 161–168. doi: 10.14483/22484728.14625.
IEEE
[1]
M. C. Parra Romero, J. F. Pantoja Benavides, y F. N. Giraldo Ramos, «Genetic algorithms for optimization and study transport tours», Vis. Electron., vol. 11, n.º 2, pp. 161–168, oct. 2017.
MLA
Parra Romero, María Camila, et al. «Genetic algorithms for optimization and study transport tours». Visión electrónica, vol. 11, n.º 2, octubre de 2017, pp. 161-8, doi:10.14483/22484728.14625.
Turabian
Parra Romero, María Camila, Jaime Francisco Pantoja Benavides, y Frank Nixon Giraldo Ramos. «Genetic algorithms for optimization and study transport tours». Visión electrónica 11, no. 2 (octubre 27, 2017): 161–168. Accedido noviembre 5, 2024. https://revistas.udistrital.edu.co/index.php/visele/article/view/14625.
Vancouver
1.
Parra Romero MC, Pantoja Benavides JF, Giraldo Ramos FN. Genetic algorithms for optimization and study transport tours. Vis. Electron. [Internet]. 27 de octubre de 2017 [citado 5 de noviembre de 2024];11(2):161-8. Disponible en: https://revistas.udistrital.edu.co/index.php/visele/article/view/14625
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