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Response time analysis of a live-cube compact storage system with two storage classes

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  • Nima Zaerpour
  • Yugang Yu
  • René B. M. de Koster

Abstract

We study a next generation of storage systems: live-cube compact storage systems. These systems are becoming increasingly popular, due to their small physical and environmental footprint paired with a large storage space. At each level of a live-cube system, multiple shuttles take care of the movement of unit loads in the x and y directions. When multiple empty locations are available, the shuttles can cooperate to create a virtual aisle for the retrieval of a desired unit load. A lift takes care of the movement across different levels in the z-direction. Two-class-based storage, in which high turnover unit loads are stored at storage locations closer to the Input/Output point, can result in a short response time. We study two-class-based storage for a live-cube system and derive closed-form formulas for the expected retrieval time. Although the system needs to be decomposed into several cases and sub-cases, we eventually obtain simple-to-use closed-form formulas to evaluate the performance of systems with any configuration and first zone boundary. Continuous-space closed-form formulas are shown to be very close to the results obtained for discrete-space live-cube systems. The numerical results show that two-class-based storage can reduce the average response time of a live-cube system by up to 55% compared with random storage for the instances tested.

Suggested Citation

  • Nima Zaerpour & Yugang Yu & René B. M. de Koster, 2017. "Response time analysis of a live-cube compact storage system with two storage classes," IISE Transactions, Taylor & Francis Journals, vol. 49(5), pages 461-480, May.
    • Handle: RePEc:taf:uiiexx:v:49:y:2017:i:5:p:461-480
    DOI: 10.1080/24725854.2016.1273563
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    References listed on IDEAS

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    1. Yugang Yu & René de Koster, 2009. "Optimal zone boundaries for two-class-based compact three-dimensional automated storage and retrieval systems," IISE Transactions, Taylor & Francis Journals, vol. 41(3), pages 194-208.
    2. Yugang Yu & René De Koster, 2012. "Sequencing heuristics for storing and retrieving unit loads in 3D compact automated warehousing systems," IISE Transactions, Taylor & Francis Journals, vol. 44(2), pages 69-87.
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    Cited by:

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    5. Jianglong Yang & Li Zhou & Huwei Liu, 2021. "Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-25, April.

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