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A novel cross docking system for distributing the perishable products considering preemption: a machine learning approach

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  • Mohammad Amin Amani

    (University of Tehran)

  • Mohammad Mahdi Nasiri

    (University of Tehran)

Abstract

In this article, a new cross-docking approach with two characteristics, namely paired-doors and preemption, is developed based on the sustainable development goals (SDG12) paradigm that expresses targets to decrease the food losses throughout the supply chain. For every receiving door, there is a corresponding shipping door in front of it. The packages can only be transferred from a receiving door to its shipping counterpart. This new cross-dock is suitable for distributing the perishable products due to the products’ time-sensitive feature. The proposed cross-docking system, which is easier to implement considering the lower automation level required, is compared with the conventional approach to evaluate the new characteristics. Moreover, a genetic algorithm and grey wolf optimizer are proposed to solve the model for the large-sized problem instances. The results show that the proposed cross-docking approach can transfer the products faster than the traditional approach. Also, a predictive model is built by a machine learning algorithm based on the mathematical modeling outputs to predict the makespan by analyzing the factors such as the total product number, number of inbound and outbound vehicles, and the number of paired doors. The results showed that the predictive model could predict the makespan (with an average of 92.8%).

Suggested Citation

  • Mohammad Amin Amani & Mohammad Mahdi Nasiri, 2023. "A novel cross docking system for distributing the perishable products considering preemption: a machine learning approach," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-32, July.
    • Handle: RePEc:spr:jcomop:v:45:y:2023:i:5:d:10.1007_s10878-023-01057-y
    DOI: 10.1007/s10878-023-01057-y
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    References listed on IDEAS

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    1. Chen, Feng & Lee, Chung-Yee, 2009. "Minimizing the makespan in a two-machine cross-docking flow shop problem," European Journal of Operational Research, Elsevier, vol. 193(1), pages 59-72, February.
    2. Mohammad Mahdi Nasiri & Ali Rahbari & Frank Werner & Roya Karimi, 2018. "Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 56(19), pages 6527-6552, October.
    3. Antonino Chiarello & Manlio Gaudioso & Marcello Sammarra, 2018. "Truck synchronization at single door cross-docking terminals," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 395-447, March.
    4. Tadumadze, Giorgi & Boysen, Nils & Emde, Simon & Weidinger, Felix, 2019. "Integrated truck and workforce scheduling to accelerate the unloading of trucks," European Journal of Operational Research, Elsevier, vol. 278(1), pages 343-362.
    5. Warisa Wisittipanich & Takashi Irohara & Piya Hengmeechai, 2019. "Truck scheduling problems in the cross docking network," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 33(3), pages 420-439.
    6. Dulebenets, Maxim A., 2019. "A Delayed Start Parallel Evolutionary Algorithm for just-in-time truck scheduling at a cross-docking facility," International Journal of Production Economics, Elsevier, vol. 212(C), pages 236-258.
    7. Tadumadze, Giorgi & Boysen, Nils & Emde, Simon & Weidinger, Felix, 2019. "Integrated truck and workforce scheduling to accelerate the unloading of trucks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112842, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Ruslan Sadykov, 2012. "Scheduling incoming and outgoing trucks at cross docking terminals to minimize the storage cost," Annals of Operations Research, Springer, vol. 201(1), pages 423-440, December.
    9. Serrano, Christian & Delorme, Xavier & Dolgui, Alexandre, 2017. "Scheduling of truck arrivals, truck departures and shop-floor operation in a cross-dock platform, based on trucks loading plans," International Journal of Production Economics, Elsevier, vol. 194(C), pages 102-112.
    10. Fei Pan & Tijun Fan & Xinyi Qi & Jingyi Chen & Chong Zhang, 2021. "Truck Scheduling for Cross-Docking of Fresh Produce with Repeated Loading," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-16, June.
    11. M. H. Fazel Zarandi & H. Khorshidian & M. Akbarpour Shirazi, 2016. "A constraint programming model for the scheduling of JIT cross-docking systems with preemption," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 297-313, April.
    12. Liao, T.W. & Egbelu, P.J. & Chang, P.C., 2013. "Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations," International Journal of Production Economics, Elsevier, vol. 141(1), pages 212-229.
    13. 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.
    14. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    15. Mohammad Amin Amani & Francesco Marinello, 2022. "A Deep Learning-Based Model to Reduce Costs and Increase Productivity in the Case of Small Datasets: A Case Study in Cotton Cultivation," Agriculture, MDPI, vol. 12(2), pages 1-13, February.
    16. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    17. Rijal, Arpan & Bijvank, Marco & de Koster, René, 2019. "Integrated scheduling and assignment of trucks at unit-load cross-dock terminals with mixed service mode dock doors," European Journal of Operational Research, Elsevier, vol. 278(3), pages 752-771.
    18. Soltani, Roya & Sadjadi, Seyed Jafar, 2010. "Scheduling trucks in cross-docking systems: A robust meta-heuristics approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(5), pages 650-666, September.
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