Application of metaheuristics in the ordering of urban transport in Camagüey

Authors

  • Yoan Martínez López Universidad de Camagüey
  • Lenier Guevara Yanes Universidad de Camagüey
  • Julio Madera Quintana Universidad de Camagüey

Keywords:

metaheuristics; modelling; urban transport; decision making

Abstract

In the practice of economic, political and social activity, man needs transport as a means of satisfying various needs. In this research, metaheuristics are developed in MATLAB for the organisation of urban transport in Camagüey. These are part of a library that implements the model proposed by Baaj and Mahmassani. The computational analysis of the algorithms: Cellular Estimation Distribution Algorithm (cEDA), Simulated Annealing (SA), Variable Neighbourhood Search (VNS) and Greedy Random Adaptive Search (GRASP) was performed. Several experiments were carried out taking into account the statistical validation performed on the algorithms, where it was shown that cEDA and SA offered the best performances. Thus, the usefulness of metaheuristics to study the urban transport problem in Camagüey is evidenced.

References

Ansola, C., E. S., & Rosete, A. (2021). Una solución metaheurística al problema de planificación de rutas de autobuses escolares con flota homogénea y selección de paradas. Ingeniería, 26(2), 233-253

Baaj, M. H., y Mahmassani, H. S. (1991). An AI‐based approach for transit route system planning and design. Journal of Advanced Transportation, 25(2), 187-209.

Bello, R., García Lorenzo, M. M., Ramón-Hernández, A., Bello-Garcia, B. ., Bello-Garcia, M., Caballero, Y., Madera-Quintana, J., Rodríguez, Y., Filiberto, Y., Martínez, Y., Simón Cuevas, A., Sánchez-Ansola, E., Pérez-Pérez, A. C., & Rosete Suárez, A. (2020). Una mirada a la inteligencia artificial frente a la COVID-19 en Cuba. Revista Cubana De Transformación Digital, 1(3), 27–36.

Campos Vasquez, N., Cueva Clemente, C., Bautista Zuñiga, L. M., & Sotomayor Burga, J. L. (2022). Métodos Algorítmicos para la optimización de rutas en el Sistema del Transporte Urbano; Pérez Pérez, A.

Carrión Rico, G., & García Hernández, M. (2007). gvSIG: Sistema de Información Geográfica en Software Libre de la Generalitat Valenciana.

Ceder, A., y Wilson, N. H. (1986). Bus network design. Transportation Research Part B: Methodological, 20(4), 331-344.

Ceder, A., Yang, Y., Liu, T., y Guan, W. (2016). A case study of Beijing bus crew scheduling: a variable neighborhood‐based approach. Journal of Advanced Transportation, 50(4), 434-445.

Demšar, J. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, , 7(Jan), 1-30.

Dib, O., Moalic, L., Manier, M.-A., y Caminada, A. (2017). An advanced GA–VNS combination for multicriteria route planning in public transit networks. Expert Systems with Applications, 72, 67-82.

Feo, T. A., y Resende, M. G. (1995). Greedy randomized adaptive search procedures. Journal of global optimization, 6(2), 109-133.

Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the american statistical association, 32(200), 675-701.

González. (2012). Los tranvías de vapor en España. Una historia (casi) desconocida. Presentado en el VI Congreso de Historia Ferroviaria Vitoria Gasteiz 2012.

García, S., Herrera, F. . (2009). Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy. Evolutionary computation, , 17(3), 275-306.

García, S., Herrera, F. . (2008). Evolutionary Under-Sampling for Classification with Imbalanced Data Sets. Proposals and Taxonomy. Evolutionary Computation. .

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian journal of statistics, 65-70. Retrieved from https://www.jstor.org/stable/4615733

Iman, R. L., Davenport, J. M. (1980). Approximations of the critical region of the fbietkan statistic. Communications in Statistics-Theory and Methods, 9(6), 571-595.

Madera, J. , Alba, E., y Ochoa, A.. Parallel Estimation of Distribution Algorithms. En E. Alba, editor, Parallel Metaheuristics: A New Class of Algorithms. John Wiley & Sons, Inc., 2005.

Mahdi Amiripour, S., Mohaymany, A. S., y Ceder, A. (2015). Optimal modification of urban bus network routes using a genetic algorithm. Journal of Transportation Engineering, 141(3), 04014081.

Martínez, Y., Rodríguez-González, A.Y., Madera, J., Bethencourt Mayedo, M., Lezama, F..(2021) Cellular Estimation of Distribution Algorithm Designed to Solve the Energy Resource Management Problem Under Uncertainty. Engineering Applications of Artificial Intelligence journal, ISSN 0952- 1976,101(104231),

Martínez, Y., Oquendo, H., Caballero, Y., Guerra, L. E., Junco, R., Benítez, I., . Madera, J. (2020) a). Aplicación de la investigación de operaciones a la distribución de recursos relacionados con la COVID-19. Retos de la Dirección, 14(2), 86-105.

Martínez, Y., Rodríguez, A. Y., Madera, J., Mayedo, M., Moya, A., y Santiago, O. M. (2020) b) . Applying some EDAs and hybrid variants to the ERM problem under uncertainty. Paper presented at the Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion.

Martínez, Y., Madera, J., y Leguen, I. (2016). Algoritmos evolutivos con estimación de distribución celulares. Revista Cubana de Ciencias Informáticas, 10, 159-170.

Martínez, Y., Madera, J., Rodríguez, A. Y., y Barigye, S. (2019) a). Cellular Estimation Gaussian Algorithm for Continuous Domain. Journal of Intelligent & Fuzzy Systems, 36(5), 4957-4967.

Martínez, Y., Rodríguez, A., Madera, J., Moya, A., Morgado, B., y Mayedo, M. B. (2019) b). CUMDANCauchy-C1: a cellular EDA designed to solve the energy resource management problem under uncertainty. Paper presented at the Proceedings of the Genetic and Evolutionary Computation Conference Companion.

Mauttone, A. (2005). Optimización de recorridos y frecuencias en sistemas de transporte público urbano colectivo.

Mauttone, A., Cancela, H., y Urquhart, M. (2002). Diseño y optimización de rutas y frecuencias en el transporte colectivo urbano, modelos y algoritmos. Paper presented at the XI Congreso Chileno de Ingenierıa de Transporte.

Mauttone, A., Urquhart, M. E. (2009). A multi-objective metaheuristic approach for the transit network design problem. Public Transport, 1(4), 253-273.

Mladenović, N., Hansen, P. (1997). Variable neighborhood search. Computers & operations research, 24(11), 1097-1100.

Morris, E. A., Ortegón-Sánchez,. & Warren, J (2015). Movilidad sostenible: un proyecto viable para las ciudades cubanas [Sustainable Mobility-a viable project for Cuban cities]. Temas, (83):36–43.

Oliva, D. (2021). Metaheuristics in Machine Learning: Theory and Applications. E. H. Houssein, & S. Hinojosa (Eds.). Springer

Oyón, J. L. (1999). Transporte público y estructura urbana:(de mediados s. XIX a mediados s. XX): Gran Bretaña, Francia y países germánicos. Ecología Política(17), 17-35.

Rasjido, J., Alancay, N., Villagra, S., & Pandolfi, D. (2016). Optimización de Rutas Aplicadas al Transporte de Personas. CDD 607, 25.

Sánchez, M. G. (2015). Calesas, quitrines y ómnibus: transportación urbana en La Habana del siglo XIX. Revista Quiroga, 36-51.

Shapiro, S. S., Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591-611.

Torres, I. M. G., Cardoso, E. C. I. , Mora, J. T., Gómez, Z. M. Q., Giraldo, C. M., y Rosabal, A. G (2020). Efecto económico parcial de la covid-19 y sus resultados en Camagüey, Cuba. Retos de la Dirección, tomo 14(2):34–54.

Van Laarhoven, P. J., Aarts, E. H. (1987). Simulated annealing. In Simulated annealing: Theory and applications (pp. 7-15): Springer.

Zhao, F., Ubaka, I., y Gan, A. (2005). Transit network optimization: minimizing transfers and maximizing service coverage with an integrated simulated annealing and tabu search method. Transportation Research Record, 1923(1), 180-188.

Published

2022-08-10

How to Cite

Martínez López, Y., Guevara Yanes, L., & Madera Quintana, J. . (2022). Application of metaheuristics in the ordering of urban transport in Camagüey. Revista Cubana De Transformación Digital, 3(2), e171. Retrieved from https://rctd.uic.cu/rctd/article/view/171

Issue

Section

Originial paper