IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/vyid10.1007_s10878-020-00619-8.html
   My bibliography  Save this article

Eco-friendly container transshipment route scheduling problem with repacking operations

Author

Listed:
  • Ming Liu

    (Tongji University)

  • Rongfan Liu

    (Tongji University)

  • E Zhang

    () (Shanghai University of Finance and Economics)

  • Chengbin Chu

    (Université Paris-Est)

Abstract

Currently, a huge amount of cargo is transported via containers by liner shipping companies. Under stochastic demand, repacking operations and carbon reduction, which may lead to an increase in effectiveness and environmental improvement, have been rarely considered in previous literature. In this paper, we investigate a container transshipment route scheduling problem with repacking operations under stochastic demand and environmental protection. The problem is a combinatorial optimization problem. Lacking historical data, a chance-constrained programming model is proposed to minimize the total operating and environment-related costs. We choose two distribution-free approaches, i.e., approximation based in Markov’s Inequality and Mixed Integer Second-Order Conic Program to approximate the chance constraints. As the loses induced by unfulfilled demand are not taken into account in the above model, a scenario-based model is developed considering the loses. Risk-neutral model may provide solutions that perform poorly while considering uncertainty. To incorporate decision makers’ perspectives, therefore, we also propose a risk-averse model adopting a risk aversion measure called Conditional Value-at-Risk to meet different preferences. Finally, we conduct computational experiments based on real data to compare the performances of the modeling methods and illustrate the impacts by testing different risk levels and confidence levels.

Suggested Citation

  • Ming Liu & Rongfan Liu & E Zhang & Chengbin Chu, 0. "Eco-friendly container transshipment route scheduling problem with repacking operations," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
  • Handle: RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-020-00619-8
    DOI: 10.1007/s10878-020-00619-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-020-00619-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Ching-Ping & Huang, Hung-Hsi, 2016. "Optimal insurance contract under VaR and CVaR constraints," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 110-127.
    2. Hua Sun & Ziyou Gao & W. Szeto & Jiancheng Long & Fangxia Zhao, 2014. "A Distributionally Robust Joint Chance Constrained Optimization Model for the Dynamic Network Design Problem under Demand Uncertainty," Networks and Spatial Economics, Springer, vol. 14(3), pages 409-433, December.
    3. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    4. Wang, Shuaian, 2013. "Essential elements in tactical planning models for container liner shipping," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 84-99.
    5. Xie, Ying & Song, Dong-Ping, 2018. "Optimal planning for container prestaging, discharging, and loading processes at seaport rail terminals with uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 88-109.
    6. Bentaha, Mohand Lounes & Battaïa, Olga & Dolgui, Alexandre & Hu, S. Jack, 2015. "Second order conic approximation for disassembly line design with joint probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 247(3), pages 957-967.
    7. Kınay, Ömer Burak & Yetis Kara, Bahar & Saldanha-da-Gama, Francisco & Correia, Isabel, 2018. "Modeling the shelter site location problem using chance constraints: A case study for Istanbul," European Journal of Operational Research, Elsevier, vol. 270(1), pages 132-145.
    8. Chao, Shih-Liang & Yu, Ming-Miin & Hsieh, Wei-Fan, 2018. "Evaluating the efficiency of major container shipping companies: A framework of dynamic network DEA with shared inputs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 44-57.
    9. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    10. Liu, Kanglin & Li, Qiaofeng & Zhang, Zhi-Hai, 2019. "Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 79-101.
    11. Chen, Jingxu & Jia, Shuai & Wang, Shuaian & Liu, Zhiyuan, 2018. "Subloop-based reversal of port rotation directions for container liner shipping network alteration," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 336-361.
    12. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    13. Young Yun, Won & Mi Lee, Yu & Seok Choi, Yong, 2011. "Optimal inventory control of empty containers in inland transportation system," International Journal of Production Economics, Elsevier, vol. 133(1), pages 451-457, September.
    14. Balakrishnan, Anantaram & Karsten, Christian Vad, 2017. "Container shipping service selection and cargo routing with transshipment limits," European Journal of Operational Research, Elsevier, vol. 263(2), pages 652-663.
    15. Zhen, Lu & Hu, Yi & Wang, Shuaian & Laporte, Gilbert & Wu, Yiwei, 2019. "Fleet deployment and demand fulfillment for container shipping liners," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 15-32.
    16. Xue, Weili & Ma, Lijun & Shen, Houcai, 2015. "Optimal inventory and hedging decisions with CVaR consideration," International Journal of Production Economics, Elsevier, vol. 162(C), pages 70-82.
    17. A. Charnes & W. W. Cooper & G. H. Symonds, 1958. "Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil," Management Science, INFORMS, vol. 4(3), pages 235-263, April.
    18. Jeong, Yoonjea & Saha, Subrata & Chatterjee, Debajyoti & Moon, Ilkyeong, 2018. "Direct shipping service routes with an empty container management strategy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 123-142.
    19. Kallio, Markku & Dehghan Hardoroudi, Nasim, 2018. "Second-order stochastic dominance constrained portfolio optimization: Theory and computational tests," European Journal of Operational Research, Elsevier, vol. 264(2), pages 675-685.
    20. Ng, ManWo, 2015. "Container vessel fleet deployment for liner shipping with stochastic dependencies in shipping demand," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 79-87.
    21. Quddus, Md Abdul & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Yu, Fei & Bian, Linkan, 2018. "A two-stage chance-constrained stochastic programming model for a bio-fuel supply chain network," International Journal of Production Economics, Elsevier, vol. 195(C), pages 27-44.
    22. Koza, David Franz, 2019. "Liner shipping service scheduling and cargo allocation," European Journal of Operational Research, Elsevier, vol. 275(3), pages 897-915.
    23. Ng, ManWo, 2014. "Distribution-free vessel deployment for liner shipping," European Journal of Operational Research, Elsevier, vol. 238(3), pages 858-862.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-020-00619-8. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.