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A Time-Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion

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  • Yan Sun
  • Martin Hrušovský
  • Chen Zhang
  • Maoxiang Lang

Abstract

This study explores an operational-level container routing problem in the road-rail multimodal service network. In response to the demand for an environmentally friendly transportation, we extend the problem into a green version by using both emission charging method and bi-objective optimization to optimize the CO 2 emissions in the routing. Two uncertain factors, including capacity uncertainty of rail services and travel time uncertainty of road services, are formulated in order to improve the reliability of the routes. By using the triangular fuzzy numbers and time-dependent travel time to separately model the capacity uncertainty and travel time uncertainty, we establish a fuzzy chance-constrained mixed integer nonlinear programming model. A linearization-based exact solution strategy is designed, so that the problem can be effectively solved by any exact solution algorithm on any mathematical programming software. An empirical case is presented to demonstrate the feasibility of the proposed methods. In the case discussion, sensitivity analysis and bi-objective optimization analysis are used to find that the bi-objective optimization method is more effective than the emission charging method in lowering the CO 2 emissions for the given case. Then, we combine sensitivity analysis and fuzzy simulation to identify the best confidence value in the fuzzy chance constraint. All the discussion will help decision makers to better organize the green multimodal transportation.

Suggested Citation

  • Yan Sun & Martin Hrušovský & Chen Zhang & Maoxiang Lang, 2018. "A Time-Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion," Complexity, Hindawi, vol. 2018, pages 1-22, June.
    • Handle: RePEc:hin:complx:8645793
    DOI: 10.1155/2018/8645793
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    References listed on IDEAS

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    1. Reis, Vasco, 2014. "Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 100-120.
    2. Burak Ayar & Hande Yaman, 2012. "An intermodal multicommodity routing problem with scheduled services," Computational Optimization and Applications, Springer, vol. 53(1), pages 131-153, September.
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    1. Touzout, Faycal A. & Ladier, Anne-Laure & Hadj-Hamou, Khaled, 2022. "An assign-and-route matheuristic for the time-dependent inventory routing problem," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1081-1097.
    2. Thibault Delbart & Yves Molenbruch & Kris Braekers & An Caris, 2021. "Uncertainty in Intermodal and Synchromodal Transport: Review and Future Research Directions," Sustainability, MDPI, vol. 13(7), pages 1-25, April.
    3. Yan Sun & Xinya Li & Xia Liang & Cevin Zhang, 2019. "A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability," Sustainability, MDPI, vol. 11(9), pages 1-27, May.
    4. Yue Lu & Maoxiang Lang & Xueqiao Yu & Shiqi Li, 2019. "A Sustainable Multimodal Transport System: The Two-Echelon Location-Routing Problem with Consolidation in the Euro–China Expressway," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    5. Shuai Yu & Yuanhua Jia & Dongye Sun, 2019. "Identifying Factors that Influence the Patterns of Road Crashes Using Association Rules: A case Study from Wisconsin, United States," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    6. Dandan Chen & Yong Zhang & Liangpeng Gao & Russell G. Thompson, 2019. "Optimizing Multimodal Transportation Routes Considering Container Use," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    7. Nandi, Sandip & Granata, Giuseppe & Jana, Subrata & Ghorui, Neha & Mondal, Sankar Prasad & Bhaumik, Moumita, 2023. "Evaluation of the treatment options for COVID-19 patients using generalized hesitant fuzzy- multi criteria decision making techniques," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
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    9. Yan Sun & Xinya Li, 2019. "Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncerta," Mathematics, MDPI, vol. 7(8), pages 1-40, August.
    10. Wenjing Guo & Bilge Atasoy & Wouter Beelaerts Blokland & Rudy R. Negenborn, 2022. "Anticipatory approach for dynamic and stochastic shipment matching in hinterland synchromodal transportation," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 483-517, June.
    11. Volodymyr Polishchuk & Miroslav Kelemen & Beáta Gavurová & Costas Varotsos & Rudolf Andoga & Martin Gera & John Christodoulakis & Radovan Soušek & Jaroslaw Kozuba & Peter Blišťan & Stanislav Szabo, 2019. "A Fuzzy Model of Risk Assessment for Environmental Start-Up Projects in the Air Transport Sector," IJERPH, MDPI, vol. 16(19), pages 1-19, September.
    12. Yan Sun & Yue Lu & Cevin Zhang, 2019. "Fuzzy Linear Programming Models for a Green Logistics Center Location and Allocation Problem under Mixed Uncertainties Based on Different Carbon Dioxide Emission Reduction Methods," Sustainability, MDPI, vol. 11(22), pages 1-24, November.

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