Skip to main content
Erschienen in: Wireless Networks 7/2020

23.04.2019

Artificial intelligence and DOE: an application to school bus routing problems

verfasst von: Jonnatan Fernando Avilés-González, Jaime Mora-Vargas, Neale R. Smith, Miguel Gaston Cedillo-Campos

Erschienen in: Wireless Networks | Ausgabe 7/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper presents the implementation of simulated annealing (SA) method, an artificial intelligence technique, to solve the optimization problem known as the school bus routing problem (SBRP). A specific challenge in all artificial intelligence optimization techniques is the selection of appropriate value parameters. One contribution of this paper is the implementation of a design of experiments technique to provide statistical support for parameter selection. The SBRP is formulated as a 0–1 integer linear programming model, where the objective function is to minimize the total cost. Because this problem is combinatorial in nature, it is not possible to find exact solutions in an adequate time, calling for the use of an artificial intelligence optimization technique. The proposed technique is SA due to its modeling flexibility and processing speed. To demonstrate the performance of the proposed algorithm, several experiments with real instances were carried out, showing that the metaheuristic algorithm performs better in quality and time than the classic routing method.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Bhoi, S. K., Khilar, P. M., & Singh, M. (2006). A path selection based routing protocol for urban vehicular ad hoc network (UVAN) environment. Wireless Networks, 2, 1552–1557. Bhoi, S. K., Khilar, P. M., & Singh, M. (2006). A path selection based routing protocol for urban vehicular ad hoc network (UVAN) environment. Wireless Networks, 2, 1552–1557.
2.
Zurück zum Zitat Bargaoui, H., Mbarek, N., Togni, O., & Frikha, M. (2016). Hybrid QoS based routing protocol for inter and intra wireless mesh infrastructure communications. Wireless Networks, 22(7), 2111–2130.CrossRef Bargaoui, H., Mbarek, N., Togni, O., & Frikha, M. (2016). Hybrid QoS based routing protocol for inter and intra wireless mesh infrastructure communications. Wireless Networks, 22(7), 2111–2130.CrossRef
3.
Zurück zum Zitat Chen, W. W., & Lea, C. T. (2016). Oblivious routing in wireless mesh networks. Wireless Networks, 22(7), 2337–2353.CrossRef Chen, W. W., & Lea, C. T. (2016). Oblivious routing in wireless mesh networks. Wireless Networks, 22(7), 2337–2353.CrossRef
5.
Zurück zum Zitat Litvinchev, I., Cedillo-Campos, M., & Velarde, M. (2017). Integrating territory design and routing problems. Journal of Computer and Systems Sciences International, 56(6), 969–974.CrossRef Litvinchev, I., Cedillo-Campos, M., & Velarde, M. (2017). Integrating territory design and routing problems. Journal of Computer and Systems Sciences International, 56(6), 969–974.CrossRef
6.
Zurück zum Zitat Pham, T. A. Q., Piamrat, K., Singh, K. D., & Viho, C. (2016). QoE-based routing algorithms for H.264/SVC video over ad-hoc networks. Wireless Networks, 22(7), 2387–2402.CrossRef Pham, T. A. Q., Piamrat, K., Singh, K. D., & Viho, C. (2016). QoE-based routing algorithms for H.264/SVC video over ad-hoc networks. Wireless Networks, 22(7), 2387–2402.CrossRef
7.
Zurück zum Zitat Das, I., Lobiyal, D. K., & Katti, C. P. (2016). Multipath routing in mobile ad hoc network with probabilistic splitting of traffic. Wireless Networks, 22(7), 2287–2298.CrossRef Das, I., Lobiyal, D. K., & Katti, C. P. (2016). Multipath routing in mobile ad hoc network with probabilistic splitting of traffic. Wireless Networks, 22(7), 2287–2298.CrossRef
11.
Zurück zum Zitat Hedar, A., & Ismail, R. (2012). Simulated annealing with stochastic local search for minimum dominating set problem. International Journal of Machine Learning and Cybernetics, 3(2), 97–109.CrossRef Hedar, A., & Ismail, R. (2012). Simulated annealing with stochastic local search for minimum dominating set problem. International Journal of Machine Learning and Cybernetics, 3(2), 97–109.CrossRef
12.
Zurück zum Zitat Kim, T., & Park, B. (2013). Model and algorithm for solving school bus problem. Journal of Emerging Trends in Computing and Information Sciences, 4(8), 596–600. Kim, T., & Park, B. (2013). Model and algorithm for solving school bus problem. Journal of Emerging Trends in Computing and Information Sciences, 4(8), 596–600.
13.
Zurück zum Zitat Deliktas, D., & Ustun, O. (2017). Bus stop selection for employees with bi-particle swarm optimization approach: Case study. In International logistics and supply chain congress 2017, October (pp. 1–9). Deliktas, D., & Ustun, O. (2017). Bus stop selection for employees with bi-particle swarm optimization approach: Case study. In International logistics and supply chain congress 2017, October (pp. 1–9).
14.
Zurück zum Zitat Riera-ledesma, J., & Jose, J. (2013). A column generation approach for a school bus routing problem with resource constraints. Computers & Operations Research, 40, 566–583.CrossRef Riera-ledesma, J., & Jose, J. (2013). A column generation approach for a school bus routing problem with resource constraints. Computers & Operations Research, 40, 566–583.CrossRef
15.
Zurück zum Zitat Ben Sghaier, S., & Ben Guedria, N. (2013). Solving school bus routing problem with genetic algorithm. In 2013 international conference on advanced logistics and transport (pp. 7–12). Ben Sghaier, S., & Ben Guedria, N. (2013). Solving school bus routing problem with genetic algorithm. In 2013 international conference on advanced logistics and transport (pp. 7–12).
16.
Zurück zum Zitat Alfa, A. S., Heragu, S. S., & Chen, M. (1991). A 3-OPT based simulated annealing algorithm for vehicle routing problems. Computer and Industrial Engineering, 21(1–4), 635–639.CrossRef Alfa, A. S., Heragu, S. S., & Chen, M. (1991). A 3-OPT based simulated annealing algorithm for vehicle routing problems. Computer and Industrial Engineering, 21(1–4), 635–639.CrossRef
17.
Zurück zum Zitat Czech, Z., & Czarnas, P. (2002). Parallel simulated annealing for the vehicle routing problem with time windows. In Parallel, distributed and network-based processing (pp. 376–383). Czech, Z., & Czarnas, P. (2002). Parallel simulated annealing for the vehicle routing problem with time windows. In Parallel, distributed and network-based processing (pp. 376–383).
18.
Zurück zum Zitat Spada, M., Bierlaire, M., & Liebling, T. M. (2005). Decision-aiding methodology for the school bus routing and scheduling problem. Transportation Science, 39(4), 477–490.CrossRef Spada, M., Bierlaire, M., & Liebling, T. M. (2005). Decision-aiding methodology for the school bus routing and scheduling problem. Transportation Science, 39(4), 477–490.CrossRef
19.
Zurück zum Zitat Askarzadeh, A., Klein, C. E., Engenharia, P., & Produção, D. (2016). A population-based simulated annealing algorithm for global optimization. In 2016 IEEE international conference on systems, man, and cybernetics (SMC 2016), October 9–12, 2016 (pp. 4626–4633). Askarzadeh, A., Klein, C. E., Engenharia, P., & Produção, D. (2016). A population-based simulated annealing algorithm for global optimization. In 2016 IEEE international conference on systems, man, and cybernetics (SMC 2016), October 9–12, 2016 (pp. 4626–4633).
21.
Zurück zum Zitat Kirkpatrick, S., Gellat, C., & Vecchi, M. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680.MathSciNetCrossRef Kirkpatrick, S., Gellat, C., & Vecchi, M. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680.MathSciNetCrossRef
22.
Zurück zum Zitat Chauhan, P., Pant, M., & Deep, K. (2014). Parameter optimization of multi-pass turning using chaotic PSO. International Journal of Machine Learning and Cybernetics, 6(2), 319–337.CrossRef Chauhan, P., Pant, M., & Deep, K. (2014). Parameter optimization of multi-pass turning using chaotic PSO. International Journal of Machine Learning and Cybernetics, 6(2), 319–337.CrossRef
24.
Zurück zum Zitat Schittekat, P., Kinable, J., Sörensen, K., Sevaux, M., Spieksma, F., & Springael, J. (2013). A metaheuristic for the school bus routing problem with bus stop selection. European Journal of Operational Research, 229(2), 518–528.CrossRef Schittekat, P., Kinable, J., Sörensen, K., Sevaux, M., Spieksma, F., & Springael, J. (2013). A metaheuristic for the school bus routing problem with bus stop selection. European Journal of Operational Research, 229(2), 518–528.CrossRef
25.
Zurück zum Zitat Bektas, T., & Elmastas, S. (2007). Solving school bus routing problems through integer programming. Journal of the Operational Research Society, 58(12), 1599–1604.CrossRef Bektas, T., & Elmastas, S. (2007). Solving school bus routing problems through integer programming. Journal of the Operational Research Society, 58(12), 1599–1604.CrossRef
26.
Zurück zum Zitat Schittekat, P., Sevaux, M., & Sorensen, K. (2006). A mathematical formulation for a school bus routing problem. In 2006 International conference on service systems and service management (Vol. 2, pp. 1552–1557). Schittekat, P., Sevaux, M., & Sorensen, K. (2006). A mathematical formulation for a school bus routing problem. In 2006 International conference on service systems and service management (Vol. 2, pp. 1552–1557).
Metadaten
Titel
Artificial intelligence and DOE: an application to school bus routing problems
verfasst von
Jonnatan Fernando Avilés-González
Jaime Mora-Vargas
Neale R. Smith
Miguel Gaston Cedillo-Campos
Publikationsdatum
23.04.2019
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 7/2020
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-019-01985-w

Weitere Artikel der Ausgabe 7/2020

Wireless Networks 7/2020 Zur Ausgabe

Neuer Inhalt