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DSS approach for sustainable system design of shuttle-based storage and retrieval systems

Author

Listed:
  • Yanyan Wang

    (Shenzhen Research Institute, Shandong University
    Shandong University)

  • Jinning Qin

    (Shandong University)

  • Shandong Mou

    (Central University of Finance and Economics)

  • Ke Huang

    (Shandong University)

  • Xiaofeng Zhao

    (Shandong University)

Abstract

Automated warehousing systems need to balance operational efficiency, energy consumption and overall system cost in sustainable supply chains. This paper presents an analytical model-based Decision Support System (DSS) for sustainable system design of Shuttle-Based Storage and Retrieval System (SBS/RS). Multiple system design indicators, namely mean service time, mean energy consumption, and overall system cost, are considered in a mathematical model. A simulation model is developed to validate the accuracy of the mathematical model. Extensive numerical experiments explore the impacts of rack design and equipment operating parameters on various system performance indicators and summarize balanced equipment operating settings. Overall, this study provides an analytical-model based DSS on sustainable SBS/RS configurations for decision-making managers and system designers.

Suggested Citation

  • Yanyan Wang & Jinning Qin & Shandong Mou & Ke Huang & Xiaofeng Zhao, 2023. "DSS approach for sustainable system design of shuttle-based storage and retrieval systems," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 698-726, September.
    • Handle: RePEc:spr:flsman:v:35:y:2023:i:3:d:10.1007_s10696-022-09447-w
    DOI: 10.1007/s10696-022-09447-w
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    References listed on IDEAS

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    1. Debjit Roy & Ananth Krishnamurthy & Sunderesh Heragu & Charles Malmborg, 2012. "Performance analysis and design trade-offs in warehouses with autonomous vehicle technology," IISE Transactions, Taylor & Francis Journals, vol. 44(12), pages 1045-1060.
    2. Bipan Zou & Xianhao Xu & Yeming Gong & René de Koster, 2016. "Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems," Post-Print hal-02313400, HAL.
    3. Banu Yetkin Ekren, 2021. "A multi-objective optimisation study for the design of an AVS/RS warehouse," International Journal of Production Research, Taylor & Francis Journals, vol. 59(4), pages 1107-1126, February.
    4. Xiao Cai & Sunderesh S. Heragu & Yang Liu, 2014. "Modeling and evaluating the AVS/RS with tier-to-tier vehicles using a semi-open queueing network," IISE Transactions, Taylor & Francis Journals, vol. 46(9), pages 905-927, September.
    5. Bipan Zou & Xianhao Xu & Yeming Gong & René de Koster, 2016. "Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems," Post-Print hal-01892897, HAL.
    6. Yanyan Wang & Shandong Mou & Yaohua Wu, 2015. "Task scheduling for multi-tier shuttle warehousing systems," International Journal of Production Research, Taylor & Francis Journals, vol. 53(19), pages 5884-5895, October.
    7. Emanuele Guerrazzi & Valeria Mininno & Davide Aloini & Riccardo Dulmin & Claudio Scarpelli & Marco Sabatini, 2019. "Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    8. Elena Tappia & Debjit Roy & René de Koster & Marco Melacini, 2017. "Modeling, Analysis, and Design Insights for Shuttle-Based Compact Storage Systems," Transportation Science, INFORMS, vol. 51(1), pages 269-295, February.
    9. Zou, Bipan & Xu, Xianhao & (Yale) Gong, Yeming & De Koster, René, 2016. "Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems," European Journal of Operational Research, Elsevier, vol. 254(1), pages 51-67.
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    Cited by:

    1. Chen Qu & Eunyoung Kim, 2024. "Reviewing the Roles of AI-Integrated Technologies in Sustainable Supply Chain Management: Research Propositions and a Framework for Future Directions," Sustainability, MDPI, vol. 16(14), pages 1-27, July.

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