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Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption

Author

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  • Tarik Chargui

    (LAMIH, UMR CNRS 8201, Université Polytechnique Hauts-de-France, Le Mont Houy, 59313 Valenciennes, France
    RSAID, ENSATe, University of Abdelmalek Essaadi, Tétouan 93000, Morocco)

  • Abdelghani Bekrar

    (LAMIH, UMR CNRS 8201, Université Polytechnique Hauts-de-France, Le Mont Houy, 59313 Valenciennes, France)

  • Mohamed Reghioui

    (RSAID, ENSATe, University of Abdelmalek Essaadi, Tétouan 93000, Morocco)

  • Damien Trentesaux

    (LAMIH, UMR CNRS 8201, Université Polytechnique Hauts-de-France, Le Mont Houy, 59313 Valenciennes, France)

Abstract

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed.

Suggested Citation

  • Tarik Chargui & Abdelghani Bekrar & Mohamed Reghioui & Damien Trentesaux, 2019. "Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption," Sustainability, MDPI, vol. 11(11), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3127-:d:236797
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    1. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    2. Van Belle, Jan & Valckenaers, Paul & Cattrysse, Dirk, 2012. "Cross-docking: State of the art," Omega, Elsevier, vol. 40(6), pages 827-846.
    3. Mihalis M. Golias & Georgios K. D. Saharidis & Maria Boile & Sotirios Theofanis, 2012. "Scheduling of Inbound Trucks at a Cross-Docking Facility: Bi-Objective VS Bi-Level Modeling Approaches," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 5(1), pages 20-37, January.
    4. Boysen, Nils & Fliedner, Malte, 2010. "Cross dock scheduling: Classification, literature review and research agenda," Omega, Elsevier, vol. 38(6), pages 413-422, December.
    5. Melissa Demartini & Claudia Pinna & Bahar Aliakbarian & Flavio Tonelli & Sergio Terzi, 2018. "Soft Drink Supply Chain Sustainability: A Case Based Approach to Identify and Explain Best Practices and Key Performance Indicators," Sustainability, MDPI, vol. 10(10), pages 1-24, October.
    6. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    7. Feng Guo & Qi Liu & Dunhu Liu & Zhaoxia Guo, 2017. "On Production and Green Transportation Coordination in a Sustainable Global Supply Chain," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
    8. Fateme Heidari & Seyed Hessameddin Zegordi & Reza Tavakkoli-Moghaddam, 2018. "Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1155-1170, June.
    9. Kelsey M. Taylor & Stephan Vachon, 2018. "Empirical research on sustainable supply chains: IJPR’s contribution and research avenues," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 950-959, January.
    10. Abraham Duarte & Juan Pantrigo & Eduardo Pardo & Nenad Mladenovic, 2015. "Multi-objective variable neighborhood search: an application to combinatorial optimization problems," Journal of Global Optimization, Springer, vol. 63(3), pages 515-536, November.
    11. Piera Centobelli & Roberto Cerchione & Emilio Esposito, 2018. "Environmental Sustainability and Energy-Efficient Supply Chain Management: A Review of Research Trends and Proposed Guidelines," Energies, MDPI, vol. 11(2), pages 1-36, January.
    12. Yves Sallez & Shenle Pan & Benoit Montreuil & Thierry Berger & Eric Ballot, 2016. "On the activeness of intelligent Physical Internet containers," Post-Print hal-01491403, HAL.
    13. Andrzej Jaszkiewicz, 2004. "A Comparative Study of Multiple-Objective Metaheuristics on the Bi-Objective Set Covering Problem and the Pareto Memetic Algorithm," Annals of Operations Research, Springer, vol. 131(1), pages 135-158, October.
    14. Yu, Wooyeon & Egbelu, Pius J., 2008. "Scheduling of inbound and outbound trucks in cross docking systems with temporary storage," European Journal of Operational Research, Elsevier, vol. 184(1), pages 377-396, January.
    15. Maxim A. Dulebenets, 2018. "A Diploid Evolutionary Algorithm for Sustainable Truck Scheduling at a Cross-Docking Facility," Sustainability, MDPI, vol. 10(5), pages 1-23, April.
    16. Ladier, Anne-Laure & Alpan, Gülgün, 2016. "Cross-docking operations: Current research versus industry practice," Omega, Elsevier, vol. 62(C), pages 145-162.
    17. Konur, Dinçer & Golias, Mihalis M., 2013. "Cost-stable truck scheduling at a cross-dock facility with unknown truck arrivals: A meta-heuristic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 71-91.
    18. Dylan Jones & Mehrdad Tamiz, 2016. "A Review of Goal Programming," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 903-926, Springer.
    19. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
    20. Jaeggi, D.M. & Parks, G.T. & Kipouros, T. & Clarkson, P.J., 2008. "The development of a multi-objective Tabu Search algorithm for continuous optimisation problems," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1192-1212, March.
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    Cited by:

    1. Chargui, Tarik & Ladier, Anne-Laure & Bekrar, Abdelghani & Pan, Shenle & Trentesaux, Damien, 2022. "Towards designing and operating physical internet cross-docks: Problem specifications and research perspectives," Omega, Elsevier, vol. 111(C).
    2. Cempírek Václav & Rybicka Iwona & Ljubaj Ivica, 2019. "Development of Electromobility in Terms of Freight Transport," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 10(2), pages 23-32, November.
    3. Reza Kiani Mavi & Mark Goh & Neda Kiani Mavi & Ferry Jie & Kerry Brown & Sharon Biermann & Ahmad A. Khanfar, 2020. "Cross-Docking: A Systematic Literature Review," Sustainability, MDPI, vol. 12(11), pages 1-19, June.
    4. Feifeng Zheng & Yaxin Pang & Yinfeng Xu, 2022. "Heuristics for cross-docking scheduling of truck arrivals, truck departures and shop-floor operations," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1571-1601, July.
    5. Johan M. Bogoya & Andrés Vargas & Oliver Schütze, 2019. "The Averaged Hausdorff Distances in Multi-Objective Optimization: A Review," Mathematics, MDPI, vol. 7(10), pages 1-35, September.
    6. Abdelghani Bekrar & Abdessamad Ait El Cadi & Raca Todosijevic & Joseph Sarkis, 2021. "Digitalizing the Closing-of-the-Loop for Supply Chains: A Transportation and Blockchain Perspective," Sustainability, MDPI, vol. 13(5), pages 1-25, March.
    7. Oluwatosin Theophilus & Maxim A. Dulebenets & Junayed Pasha & Olumide F. Abioye & Masoud Kavoosi, 2019. "Truck Scheduling at Cross-Docking Terminals: A Follow-Up State-Of-The-Art Review," Sustainability, MDPI, vol. 11(19), pages 1-23, September.

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