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Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths

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  • Wan-Yu Liu

    (Department of Tourism Information, Aletheia University, New Taipei City 251, Taiwan)

  • Chun-Cheng Lin

    (Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan)

  • Ching-Ren Chiu

    (Institute of Service Management, National Penghu University of Science and Technology, Penghu 880, Taiwan)

  • You-Song Tsao

    (Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan)

  • Qunwei Wang

    (School of Business, Soochow University, Suzhou 215006, China)

Abstract

Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA) to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.

Suggested Citation

  • Wan-Yu Liu & Chun-Cheng Lin & Ching-Ren Chiu & You-Song Tsao & Qunwei Wang, 2014. "Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths," Sustainability, MDPI, vol. 6(7), pages 1-27, July.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:7:p:4658-4684:d:38481
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    References listed on IDEAS

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    Cited by:

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    3. Gaoyuan Qin & Fengming Tao & Lixia Li, 2019. "A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions," IJERPH, MDPI, vol. 16(4), pages 1-17, February.
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    7. Ziqi Wang & Peihan Wen, 2020. "Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window," Sustainability, MDPI, vol. 12(5), pages 1-22, March.
    8. Songyi Wang & Fengming Tao & Yuhe Shi & Haolin Wen, 2017. "Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax," Sustainability, MDPI, vol. 9(5), pages 1-23, April.
    9. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    10. Ozgur Kabadurmus & Mehmet S. Erdogan, 2023. "A green vehicle routing problem with multi-depot, multi-tour, heterogeneous fleet and split deliveries: a mathematical model and heuristic approach," Journal of Combinatorial Optimization, Springer, vol. 45(3), pages 1-29, April.
    11. Xujing Zhang & Lichuan Wang & Yan Chen, 2019. "Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)," Sustainability, MDPI, vol. 11(9), pages 1-15, May.
    12. Shijin Wang & Xiaodong Wang & Xin Liu & Jianbo Yu, 2018. "A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction," Sustainability, MDPI, vol. 10(11), pages 1-21, November.
    13. Yuhe Shi & Zhenggang He, 2018. "Decision Analysis of Disturbance Management in the Process of Medical Supplies Transportation after Natural Disasters," IJERPH, MDPI, vol. 15(8), pages 1-18, August.
    14. Songyi Wang & Fengming Tao & Yuhe Shi, 2018. "Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint," IJERPH, MDPI, vol. 15(1), pages 1-17, January.
    15. Lorena Reyes-Rubiano & Laura Calvet & Angel A. Juan & Javier Faulin & Lluc Bové, 2020. "A biased-randomized variable neighborhood search for sustainable multi-depot vehicle routing problems," Journal of Heuristics, Springer, vol. 26(3), pages 401-422, June.

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