The uncertainty of transportation duration between nodes is an inherent characteristic and should be concerned in the routing optimization of the multimodal transportation network to guarantee the reliability of delivery time. The interval number is used to deal with the uncertainty of transportation duration, and the multi-objective robust optimization model is established which covers the transportation duration and the cost. To solve the combinatorial optimization problem of this study, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is designed, which integrates the (μ + λ) selection method elite retention and the external filing elite retention. Our findings verify the efficiency of the proposed approach by analyzing the diversity, distribution and convergence of the frontier solutions. Finally, near-optimal solutions are obtained with the proposed algorithm in the numerical example. The present study can provide decision reference for multimodal transportation carriers in making transportation plan under uncertainty.
Keywords: Multimodal transportation, multi-objective, route optimization, uncertainty, NSGA-II
@article{RO_2021__55_S1_S3035_0,
author = {Peng, Yong and Yong, Pengcheng and Luo, Yijuan},
title = {The route problem of multimodal transportation with timetable under uncertainty: multi-objective robust optimization model and heuristic approach},
journal = {RAIRO. Operations Research},
pages = {S3035--S3050},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
doi = {10.1051/ro/2020110},
mrnumber = {4223178},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2020110/}
}
TY - JOUR AU - Peng, Yong AU - Yong, Pengcheng AU - Luo, Yijuan TI - The route problem of multimodal transportation with timetable under uncertainty: multi-objective robust optimization model and heuristic approach JO - RAIRO. Operations Research PY - 2021 SP - S3035 EP - S3050 VL - 55 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2020110/ DO - 10.1051/ro/2020110 LA - en ID - RO_2021__55_S1_S3035_0 ER -
%0 Journal Article %A Peng, Yong %A Yong, Pengcheng %A Luo, Yijuan %T The route problem of multimodal transportation with timetable under uncertainty: multi-objective robust optimization model and heuristic approach %J RAIRO. Operations Research %D 2021 %P S3035-S3050 %V 55 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2020110/ %R 10.1051/ro/2020110 %G en %F RO_2021__55_S1_S3035_0
Peng, Yong; Yong, Pengcheng; Luo, Yijuan. The route problem of multimodal transportation with timetable under uncertainty: multi-objective robust optimization model and heuristic approach. RAIRO. Operations Research, Tome 55 (2021), pp. S3035-S3050. doi: 10.1051/ro/2020110
[1] , and , Robust optimisation of the intermodal freight transport problem: modeling and solving with an efficient hybrid approach. J. Comput. Sci. 30 (2019) 127–142. | DOI
[2] , and , Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion. Transp. Res. Part E: Logistics Transp. Rev. 76 (2015) 45–57. | DOI
[3] , , and , A parallel algorithm for solving time dependent multimodal transport problem [C]. In: International IEEE Conference on Intelligent Transportation Systems. IEEE, Washington, DC (2011).
[4] and , Optimized load planning of trains in intermodal transportation. OR Spectrum 34 (2012) 511–533. | MR | Zbl | DOI
[5] , Best routes selection in international intermodal networks. J. Dalian Maritime Univ. 35 (2008) 2877–2891. | Zbl
[6] , , , and , An intermodal transport network planning algorithm using dynamic programming. Appl. Intell. 36 (2012) 529–541. | DOI
[7] , , and , A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6 (2002) 182–197. | DOI
[8] , , , , and , A green intermodal service network design problem with travel time uncertainty. Transp. Res. Part B: Methodol. 93 (2016) 789–807. | DOI
[9] , and , Location-routing problem in multimodal transportation network with time windows and fuzzy demands: presenting a two-part genetic algorithm. Comput. Ind. Eng. 119 (2018) 233–246. | DOI
[10] , and , Artificial Intelligence Through Simulated Evolution. John Wiley & Sons, New York, NY (1966). | Zbl
[11] and , An integrated location and routing approach for transporting hazardous materials in a bi-modal transportation network. Transp. Res. Part E: Logistics Transp. Rev. 127 (2019) 49–65. | DOI
[12] , Dynamic approach to strategic and operational multimodal routing decisions. Int. J. Logistics Syst. Manage. 2 (2006) 96. | DOI
[13] and , Optimization on combination of transport routes and modes on dynamic programming for a container multimodal transport system. Proc. Eng. 137 (2016) 382–390. | DOI
[14] , , and , Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty. Flexible Serv. Manuf. J. 30 (2016) 486–516. | DOI
[15] and , A market-oriented approach for intermodal network optimization meeting cost, time and environmental requirements. Int. J. Prod. Econ. 171 (2016) 266–274. | DOI
[16] , and , Intermodal freight transport planning – A receding horizon control approach. Transp. Res. Part C: Emerg. Technol. 60 (2015) 77–95. | DOI
[17] , , and , The robust shortest path problem for multimodal transportation considering timetable with interval data. Syst. Sci. Control Eng. 6 (2018) 68–78. | DOI
[18] and , Assessing policy measures for the stimulation of intermodal transport: a GIS-based policy analysis. J. Transp. Geogr. 17 (2009) 500–508. | DOI
[19] , , , and , Solving a bi-objective transportation location routing problem by metaheuristic algorithms. Eur. J. Oper. Res. 234 (2014) 25–36. | MR | Zbl | DOI
[20] and , An improved version of the augmented -constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems. Appl. Math. Comput. 219 (2013) 9652–9669. | MR | Zbl
[21] and , Firework algorithm for multi-objective optimization of a multimodal transportation network problem. Proc. Comput. Sci. 112 (2017) 1670–1682. | DOI
[22] , Methods and Applications of Interval Analysis. Vol 2 of Studies in Applied and Numerical Mathematics. SIAM, Philadelphia, PA (1979). | MR | Zbl
[23] and , Design and operation of intermodal transportation network in the Marmara region of Turkey. Transp. Res. Part E: Logistics Transp. Rev. 83 (2015) 16–33. | DOI
[24] , Fault tolerant design using single and multi-criteria genetic algorithms. Masters Thesis, Massachusetts Institute of Technology (1995).
[25] and , Shortest path problem of uncertain random network. Comput. Ind. Eng. 99 (2016) 97–105. | DOI
[26] , , , and , Multimodal freight transportation planning: a literature review. Eur. J. Oper. Res. 233 (2014) 1–15. | DOI
[27] and , Intermodal containerized shipping in foreign trade and regional accessibility advantages. J. Transp. Geogr. 18 (2010) 530–547. | DOI
[28] and , Discrete intermodal freight transportation network design with route choice behavior of intermodal operators. Transp. Res. Part B Methodol. 95 (2017) 76–104. | DOI
[29] , and , The constrained shortest path problem with stochastic correlated link travel times. Eur. J. Oper. Res. 255 (2016) 43–57. | MR | DOI
[30] , , and , Modeling and optimization of a road-rail intermodal transport system under uncertain information. Eng. App. Artif. Intell. 72 (2018) 423–436. | DOI
[31] and , Import-export freight organization and optimization in the dry-port-based cross-border logistics network under the Belt and Road Initiative. Comput. Ind. Eng. 130 (2019) 472–484. | DOI
[32] , , and , Designing multimodal freight transport networks: a heuristic approach and applications. Transp. Sci. 43 (2009) 129–143. | DOI
[33] , and , Bi-objective modelling for hazardous materials road-rail multimodal routing problem with railway schedule-based space-time constraints. Int. J. Environ. Res. Public Health 13 (2016) 1–31.
[34] , and , Analysis of intermodal freight from China to Indian Ocean: a goal programming approach. J. Transp. Geogr. 19 (2011) 515–527. | DOI
[35] , and , Planning and optimization of intermodal hub-and-spoke network under mixed uncertainty. Transp. Res. Part E: Logistics Transp. Rev. 95 (2016) 248–266. | DOI
[36] , , and , Capacitated location-routing problem with time windows under uncertainty. Knowl.-Based Syst. 37 (2013) 480–489. | DOI
[37] , and , Modeling and optimization of a container drayage problem with resource constraints. Int. J. Prod. Econ. 133 (2011) 351–359. | DOI
[38] , and , A Study on the Paths Choice of Intermodal Transport Based on Reliability, in , , , (eds) LISS 2014. Springer, Berlin-Heidelberg (2015) 305–315.
[39] , , and , A bi-objective model for uncertain multi-modal shortest path problems. J. Uncertainty Anal. App. 3 (2015) 8. | DOI
[40] and , Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3 (1999) 257–271. | DOI
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