Skip to main content

2024 | OriginalPaper | Buchkapitel

Cooperative Coevolution for Cross-City Itinerary Planning

verfasst von : Ziyu Zhang, Peilan Xu, Zhaoguo Wang, Wenjian Luo

Erschienen in: Intelligent Information Processing XII

Verlag: Springer Nature Switzerland

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

search-config
loading …

Abstract

The itinerary planning problem plays a pivotal role in the tourism industry, involving the selection of an optimal tour route from multiple preferred points of interest (POIs) chosen by travelers while considering their diverse needs. However, as tourism expands and transportation becomes more accessible, there is a growing preference among travelers for planning single trips across multiple cities-referred to as cross-city itinerary planning. This paper introduces a novel approach, called CCIP, the cooperative coevolution framework for cross-city itinerary planning, which employs a divide-and-conquer method to automatically devise scalable cross-city itineraries, accounting for travelers’ preferences regarding time and travel choices. Experimental evaluations on real datasets from various cities in Jiangsu Province demonstrate that the proposed algorithm outperforms two classical multi-objective optimization algorithms, as measured by the HV metric.

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 Castillo, L., et al.: SAMAP: an user-oriented adaptive system for planning tourist visits. Expert Syst. Appl. 34(2), 1318–1332 (2008)CrossRef Castillo, L., et al.: SAMAP: an user-oriented adaptive system for planning tourist visits. Expert Syst. Appl. 34(2), 1318–1332 (2008)CrossRef
2.
Zurück zum Zitat Chang, H.T., Chang, Y.M., Tsai, M.T.: ATIPS: automatic travel itinerary planning system for domestic areas. Computat. Intell. Neurosci. 2016 (2015) Chang, H.T., Chang, Y.M., Tsai, M.T.: ATIPS: automatic travel itinerary planning system for domestic areas. Computat. Intell. Neurosci. 2016 (2015)
3.
Zurück zum Zitat Chen, C., Zhang, D., Guo, B., Ma, X., Pan, G., Wu, Z.: TripPlanner: personalized trip planning leveraging heterogeneous crowdsourced digital footprints. IEEE Trans. Intell. Transp. Syst. 16(3), 1259–1273 (2015)CrossRef Chen, C., Zhang, D., Guo, B., Ma, X., Pan, G., Wu, Z.: TripPlanner: personalized trip planning leveraging heterogeneous crowdsourced digital footprints. IEEE Trans. Intell. Transp. Syst. 16(3), 1259–1273 (2015)CrossRef
4.
Zurück zum Zitat Chen, G., Wu, S., Zhou, J., Tung, A.K.: Automatic itinerary planning for traveling services. IEEE Trans. Knowl. Data Eng. 26(3), 514–527 (2014)CrossRef Chen, G., Wu, S., Zhou, J., Tung, A.K.: Automatic itinerary planning for traveling services. IEEE Trans. Knowl. Data Eng. 26(3), 514–527 (2014)CrossRef
5.
Zurück zum Zitat Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)CrossRef Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)CrossRef
6.
Zurück zum Zitat Hu, W., Fathi, M., Pardalos, P.M.: A multi-objective evolutionary algorithm based on decomposition and constraint programming for the multi-objective team orienteering problem with time windows. Appl. Soft Comput. 73, 383–393 (2018)CrossRef Hu, W., Fathi, M., Pardalos, P.M.: A multi-objective evolutionary algorithm based on decomposition and constraint programming for the multi-objective team orienteering problem with time windows. Appl. Soft Comput. 73, 383–393 (2018)CrossRef
7.
Zurück zum Zitat Huang, T., Gong, Y.J., Zhang, Y.H., Zhan, Z.H., Zhang, J.: Automatic planning of multiple itineraries: a niching genetic evolution approach. IEEE Trans. Intell. Transp. Syst. 21(10), 4225–4240 (2019) CrossRef Huang, T., Gong, Y.J., Zhang, Y.H., Zhan, Z.H., Zhang, J.: Automatic planning of multiple itineraries: a niching genetic evolution approach. IEEE Trans. Intell. Transp. Syst. 21(10), 4225–4240 (2019) CrossRef
8.
Zurück zum Zitat Luo, W., Qiao, Y., Lin, X., Xu, P., Preuss, M.: Many-modal optimization by difficulty-based cooperative co-evolution. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1907–1914. IEEE (2019) Luo, W., Qiao, Y., Lin, X., Xu, P., Preuss, M.: Many-modal optimization by difficulty-based cooperative co-evolution. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1907–1914. IEEE (2019)
9.
Zurück zum Zitat Ma, Z., Guo, H., Gui, Y., Gong, Y.J.: An efficient computational approach for automatic itinerary planning on web servers. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 991–999 (2021) Ma, Z., Guo, H., Gui, Y., Gong, Y.J.: An efficient computational approach for automatic itinerary planning on web servers. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 991–999 (2021)
10.
Zurück zum Zitat Moore, J.: Application of particle swarm to multiobjective optimization. Technical report (1999) Moore, J.: Application of particle swarm to multiobjective optimization. Technical report (1999)
11.
Zurück zum Zitat Omidvar, M.N., Kazimipour, B., Li, X., Yao, X.: CBCC3-a contribution-based cooperative co-evolutionary algorithm with improved exploration/exploitation balance. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 3541–3548. IEEE (2016) Omidvar, M.N., Kazimipour, B., Li, X., Yao, X.: CBCC3-a contribution-based cooperative co-evolutionary algorithm with improved exploration/exploitation balance. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 3541–3548. IEEE (2016)
12.
Zurück zum Zitat Omidvar, M.N., Li, X., Yao, X.: Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, pp. 1115–1122 (2011) Omidvar, M.N., Li, X., Yao, X.: Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, pp. 1115–1122 (2011)
14.
Zurück zum Zitat Qiao, Y., Luo, W., Lin, X., Xu, P., Preuss, M.: DBCC2: an improved difficulty-based cooperative co-evolution for many-modal optimization. Complex Intell. Syst. 1–21 (2023) Qiao, Y., Luo, W., Lin, X., Xu, P., Preuss, M.: DBCC2: an improved difficulty-based cooperative co-evolution for many-modal optimization. Complex Intell. Syst. 1–21 (2023)
15.
Zurück zum Zitat Rodríguez, B., Molina, J., Pérez, F., Caballero, R.: Interactive design of personalised tourism routes. Tour. Manag. 33(4), 926–940 (2012)CrossRef Rodríguez, B., Molina, J., Pérez, F., Caballero, R.: Interactive design of personalised tourism routes. Tour. Manag. 33(4), 926–940 (2012)CrossRef
16.
Zurück zum Zitat Ruiz-Meza, J., Montoya-Torres, J.R.: A systematic literature review for the tourist trip design problem: extensions, solution techniques and future research lines. Oper. Res. Perspect. 9, 100228 (2022)MathSciNet Ruiz-Meza, J., Montoya-Torres, J.R.: A systematic literature review for the tourist trip design problem: extensions, solution techniques and future research lines. Oper. Res. Perspect. 9, 100228 (2022)MathSciNet
18.
Zurück zum Zitat Vincent, F.Y., Jewpanya, P., Ting, C.J., Redi, A.P.: Two-level particle swarm optimization for the multi-modal team orienteering problem with time windows. Appl. Soft Comput. 61, 1022–1040 (2017)CrossRef Vincent, F.Y., Jewpanya, P., Ting, C.J., Redi, A.P.: Two-level particle swarm optimization for the multi-modal team orienteering problem with time windows. Appl. Soft Comput. 61, 1022–1040 (2017)CrossRef
19.
Zurück zum Zitat Wang, X., et al.: Analysis of changes in population’s cross-city travel patterns in the pre-and post-pandemic era: a case study of china. Cities 122, 103472 (2022)CrossRef Wang, X., et al.: Analysis of changes in population’s cross-city travel patterns in the pre-and post-pandemic era: a case study of china. Cities 122, 103472 (2022)CrossRef
20.
Zurück zum Zitat Xu, P., Luo, W., Lin, X., Chang, Y., Tang, K.: Difficulty and contribution-based cooperative coevolution for large-scale optimization. IEEE Trans. Evol. Comput. 27(5), 1355–1369 (2023)CrossRef Xu, P., Luo, W., Lin, X., Chang, Y., Tang, K.: Difficulty and contribution-based cooperative coevolution for large-scale optimization. IEEE Trans. Evol. Comput. 27(5), 1355–1369 (2023)CrossRef
21.
Zurück zum Zitat Xu, P., Luo, W., Lin, X., Zhang, J., Qiao, Y., Wang, X.: Constraint-objective cooperative coevolution for large-scale constrained optimization. ACM Trans. Evol. Learn. Optim. 1(3), 1–26 (2021)CrossRef Xu, P., Luo, W., Lin, X., Zhang, J., Qiao, Y., Wang, X.: Constraint-objective cooperative coevolution for large-scale constrained optimization. ACM Trans. Evol. Learn. Optim. 1(3), 1–26 (2021)CrossRef
22.
Zurück zum Zitat Xu, P., Luo, W., Lin, X., Zhang, J., Wang, X.: A large-scale continuous optimization benchmark suite with versatile coupled heterogeneous modules. Swarm Evol. Comput. 78, 101280 (2023)CrossRef Xu, P., Luo, W., Lin, X., Zhang, J., Wang, X.: A large-scale continuous optimization benchmark suite with versatile coupled heterogeneous modules. Swarm Evol. Comput. 78, 101280 (2023)CrossRef
24.
Zurück zum Zitat Xu, P., Luo, W., Xu, J., Qiao, Y., Zhang, J., Gu, N.: An alternative way of evolutionary multimodal optimization: density-based population initialization strategy. Swarm Evol. Comput. 67, 100971 (2021)CrossRef Xu, P., Luo, W., Xu, J., Qiao, Y., Zhang, J., Gu, N.: An alternative way of evolutionary multimodal optimization: density-based population initialization strategy. Swarm Evol. Comput. 67, 100971 (2021)CrossRef
25.
Zurück zum Zitat Zhang, Q., Li, H.: MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712–731 (2007)CrossRef Zhang, Q., Li, H.: MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712–731 (2007)CrossRef
26.
Zurück zum Zitat Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans. Evol. Comput. 3(4), 257–271 (1999)CrossRef Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans. Evol. Comput. 3(4), 257–271 (1999)CrossRef
27.
Zurück zum Zitat Zografos, K.G., Androutsopoulos, K.N.: Algorithms for itinerary planning in multimodal transportation networks. IEEE Trans. Intell. Transp. Syst. 9(1), 175–184 (2008)CrossRef Zografos, K.G., Androutsopoulos, K.N.: Algorithms for itinerary planning in multimodal transportation networks. IEEE Trans. Intell. Transp. Syst. 9(1), 175–184 (2008)CrossRef
Metadaten
Titel
Cooperative Coevolution for Cross-City Itinerary Planning
verfasst von
Ziyu Zhang
Peilan Xu
Zhaoguo Wang
Wenjian Luo
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-57808-3_28