An analytical approach for a performance calculation of shuttle-based storage and retrieval systems with multiple-deep and class-based storage

References

• Azadeh, K., Roy, D., & De Koster, R. (2019). Design, modeling, and analysis of vertical robotic storage and retrieval systems. Transportation Science, 53(5), 1213–1234. https://doi.org/10.1287/trsc.2018.0883
   Web of Science ®Google Scholar
• Boysen, N., De Koster, R., & Weidinger, F. (2019). Warehousing in the e-commerce era: A survey. European Journal of Operational Research, 277(2), 396–411. https://doi.org/10.1016/j.ejor.2018.08.023
   Web of Science ®Google Scholar
• Carlo, H. J., & Vis, I. F. A. (2012). Sequencing dynamic storage systems with multiple lifts and shuttles. International Journal of Production Economics, 140(2), 844–853. https://doi.org/10.1016/j.ijpe.2012.06.035
   Web of Science ®Google Scholar
• Eder, M., & Kartnig, G. (2016). Throughput analysis of S/R shuttle systems and ideal geometry for high performance. FME Transactions, 44(2), 174–179. https://doi.org/10.5937/fmet1602174E
   Web of Science ®Google Scholar
• Eder, M. (2019). An analytical approach for a performance calculation of shuttle-based storage and retrieval systems. Production & Manufacturing Research, 7(1), 255–270. https://doi.org/10.1080/21693277.2019.1619102
   Web of Science ®Google Scholar
• Eder, M. (2020a). An approach for a performance calculation of shuttle-based storage and retrieval systems with multiple-deep storage. The International Journal of Advanced Manufacturing Technology, 107, 859–873. https://doi.org/10.1007/s00170-019-04831-7
   Google Scholar
• Eder, M. (2020b). Analytical model to estimate the performance of shuttle-based storage and retrieval systems with class-based storage policy. The International Journal of Advanced Manufacturing Technology, 107, 2091–2106. https://doi.org/10.1007/s00170-020-04990-y
   Google Scholar
• Ekren, B. Y., Sari, Z., & Lerher, T. (2015). Warehouse design under class-based storage policy of shuttle-based storage and retrieval system. IFAC-PapersOnLine, 48(3), 1152–1154. https://doi.org/10.1016/j.ifacol.2015.06.239
   Google Scholar
• Ekren, B. Y., et al. 2017. “A queuing network approach for performance estimation of shuttle based storage and retrieval system design.” In B. Y. Ekren, A. Akpunar, Z. Sari, T. Lerher (Eds.), XXII international conference on material handling constructions and logistics - MHCL 2017.
   Google Scholar
• Epp, M., Wiedemann, S., & Furmans, K. (2017). A discrete-time queueing network approach to performance evaluation of autonomous vehicle storage and retrieval systems. International Journal of Production Research, 55(4), 960–978. https://doi.org/10.1080/00207543.2016.1208371
   Web of Science ®Google Scholar
• Heragu, S. S., Cai, X., Krishnamurthy, A., & Malmborg, C. J. (2011). Analytical models for analysis of automated warehouse material handling systems. International Journal of Production Research, 49(22), 6833–6861. https://doi.org/10.1080/00207543.2010.518994
   Web of Science ®Google Scholar
• Jerman, B., Yetkin Ekren, B., Küçükyaşar, M., & Lerher, T. (2021). Simulation- based performance analysis for a novel avs/rs technology with movable lifts. Applied Sciences, 11(5), 2283. https://doi.org/10.3390/app11052283
   Google Scholar
• Kriehn, T., Schloz, F., Wehking, K.-H., & Fittinghoff, M. (2018). Impact of class-based storage, sequencing of retrieval requests and warehouse reorganisation on throughput of shuttle-based storage and retrieval systems. FME Transactions, 46(3), 320–329. https://doi.org/10.5937/fmet1803320K
   Web of Science ®Google Scholar
• Kuo, P.-H., Krishnamurthy, A., & Malmborg, C. J. (2008). Performance modelling of autonomous vehicle storage and retrieval systems using class-based storage policies. International Journal of Computer Applications in Technology, 31(3–4), 238–248. https://doi.org/10.1504/IJCAT.2008.018160
   Google Scholar
• Lehmann, T., & Hußmann, J. (2021). Travel time model for multi-deep automated storage and retrieval system with a homogeneous allocation structure. Logistics Research, 14, 5. https://doi.org/10.23773/2021_5
   Google Scholar
• Lerher, T. (2016). Travel time model for double-deep shuttle-based storage and retrieval systems. International Journal of Production Research, 54(9), 2519–2540. https://doi.org/10.1080/00207543.2015.1061717
   Web of Science ®Google Scholar
• Lin, Y., Wang, Y., Zhu, J., & Wang, L. (2021). A model and a task scheduling method for double-deep tier-captive SBS/RS with alternative elevator-patterns. IEEE Access, 9, 146378–146391. https://doi.org/10.1109/ACCESS.2021.3120418
   Web of Science ®Google Scholar
• Liu, Z., Wang, Y., Jin, M., Hao, W., & Dong, W. (2021). Energy consumption model for shuttle-based storage and retrieval systems. Journal of Cleaner Production, 282, 124480. https://doi.org/10.1016/j.jclepro.2020.124480
   Web of Science ®Google Scholar
• Manzini, R., Accorsi, R., Baruffaldi, G., Cennerazzo, T., & Gamberi, M. (2016). Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS). International Journal of Production Research, 54(14), 4286–4304. https://doi.org/10.1080/00207543.2016.1144241
   Web of Science ®Google Scholar
• Marchet, G., Melacini, M., Perotti, S., & Tappia, E. (2012). Analytical model to estimate performances of autonomous vehicle storage and retrieval systems for product totes. International Journal of Production Research, 50(24), 7134–7148. https://doi.org/10.1080/00207543.2011.639815
   Web of Science ®Google Scholar
• Marolt, J., Kosanić, N., & Lerher, T. (2022). Relocation and storage assignment strategy evaluation in a multiple-deep tier captive automated vehicle storage and retrieval system with undetermined retrieval sequence. The International Journal of Advanced Manufacturing Technology, 118(9), 3403–3420. https://doi.org/10.1007/s00170-021-08169-x
   Web of Science ®Google Scholar
• Schloz, F., Kriehn, T., Wehking, K.-H., & Fittinghoff, M. (2017). Entwicklung situationsabhängiger Lagerstrategien für Hochregallager mit autonomen Fahrzeugen. Logistics Journal: Proceedings, 2017(10), 1–8 https://doi.org/10.2195/lj_Proc_schloz_de_201710_01
   Google Scholar
• Silva, A., Coelho, L. C., Darvish, M., & Renaud, J. (2020). Integrating storage location and order picking problems in warehouse planning. Transportation Research Part E: Logistics and Transportation Review, 140, 102003. https://doi.org/10.1016/j.tre.2020.102003
   Web of Science ®Google Scholar
• Smith, J. M. (2004). Optimal design and performance modelling of M/G/1/K queueing systems. Mathematical and Computer Modelling, 39(9–10), 1049–1081. https://doi.org/10.1016/S0895-7177(04)90534-1
   Google Scholar
• Tappia, E., Roy, D., De Koster, R., & Melacini, M. (2017). Modeling, analysis, and design insights for shuttle-based compact storage systems. Transportation Science, 51(1), 269–295. https://doi.org/10.1287/trsc.2016.0699
   Web of Science ®Google Scholar
• Zhan, X., Liyun, X., & Ling, X. (2021). Task scheduling problem of double-deep multi-tier shuttle warehousing systems. Processes, 9(1), 41. https://doi.org/10.3390/pr9010041
   Web of Science ®Google Scholar