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Scheduling automated guided vehicles in very narrow aisle warehouses

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  • Polten, Lukas
  • Emde, Simon

Abstract

In this paper, we study the scheduling of storage and retrieval of unit loads from very narrow aisles using automated guided vehicles (AGVs). As AGVs cannot pass each other in the aisles, sequencing the aisle access is essential. We propose two access policies, present multiple complexity results and formulate MIP models. We then present a large neighborhood search that produces solutions within less than 2.5% of the optimum solution on average in a short amount of time for instances with hundreds of jobs. We use our heuristic to derive insights into the best access policy, number of AGVs, as well as the optimal layout of very narrow aisle warehouses.

Suggested Citation

  • Polten, Lukas & Emde, Simon, 2021. "Scheduling automated guided vehicles in very narrow aisle warehouses," Omega, Elsevier, vol. 99(C).
    • Handle: RePEc:eee:jomega:v:99:y:2021:i:c:s0305048318304729
    DOI: 10.1016/j.omega.2020.102204
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    Cited by:

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    3. Ilias Vlachos & Rodrigo Martinez Pascazzi & Miltiadis Ntotis & Konstantina Spanaki & Stella Despoudi & Panagiotis Repoussis, 2022. "Smart and flexible manufacturing systems using Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT)," Post-Print hal-03825237, HAL.
    4. Weikang Fang & Zailin Guan & Peiyue Su & Dan Luo & Linshan Ding & Lei Yue, 2022. "Multi-Objective Material Logistics Planning with Discrete Split Deliveries Using a Hybrid NSGA-II Algorithm," Mathematics, MDPI, vol. 10(16), pages 1-30, August.
    5. Justkowiak, Jan-Erik & Pesch, Erwin, 2023. "A column generation driven heuristic for order-scheduling and rack-sequencing in robotic mobile fulfillment systems," Omega, Elsevier, vol. 120(C).

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