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Motion and layout planning in a grid-based early baggage storage system

Heuristic algorithms and a simulation study
  • Altan Yalcin
  • Achim KobersteinEmail author
  • Kai-Oliver Schocke
Regular Article


Grid-based storage systems consist of many adjacent square cells arranged in a rectangular grid. Cells are either empty or occupied by a storage item. Items are stored on conveyors and are movable simultaneously and independently into the four cardinal directions. This technology allows for very dense storage. Previous research on grid-based storages has mainly focused on retrieval performance analysis of a single storage item. In this paper, we contribute a framework for the efficient storage and retrieval of a large number of storage items based on a multi-agent routing algorithm. We evaluate the framework using different storage and retrieval strategies in a simulation-based case study, in which we design and analyze a grid-based early baggage storage system at a major German airport.


Grid-based storage Puzzle-based storage High-density storage Multi-agent routing Simulation Airport logistics Early baggage storage 



The present study was financially supported by Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz mit der Förderlinie 3: LOEWE-KMU-Verbundvorhaben of Hesses Ministry of Higher Education, Research, and Arts from the research funding program (Grant No. HA 405/13-44), (Grant No. HA 422/14-32).


  1. Alfieri A, Cantamessa M, Monchiero A, Montagna F (2010) Heuristics for puzzle-based storage systems driven by a limited set of automated guided vehicles. J Intell Manuf 23(5):1695–1705CrossRefGoogle Scholar
  2. Desaulniers G, Langevin A, Riopel D, Villeneuve B (2003) Dispatching and conflict-free routing of automated guided vehicles: an exact approach. Int J Flex Manuf Syst 15(4):309–331CrossRefGoogle Scholar
  3. Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1(1):269–271CrossRefGoogle Scholar
  4. Doppler (2016) DCS 2DL. Accessed 06 Dec 2016
  5. Gebhardt (2016) Gebhardt flexconveyor. Accessed 06 Dec 2016
  6. Gue KR (2006) Very high density storage systems. IIE Trans 38:79–90CrossRefGoogle Scholar
  7. Gue KR, Kim S (2007) Puzzle-based storage systems. Nav Res Logist 54(5):556–567CrossRefGoogle Scholar
  8. Gue KR, Furmans K, Seibold Z, Uludag O (2014) Gridstore: a puzzle-based storage system with decentralized control. IEEE Trans Autom Sci Eng 11(2):429–438CrossRefGoogle Scholar
  9. Hart P, Nilsson N, Raphael B (1968) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cyber 4(2):100–107CrossRefGoogle Scholar
  10. Hatzack W, Nebel B (2014) The operational traffic control problem: computational complexity and solutions. In: 6th European conference on planningGoogle Scholar
  11. Hyundai Elevator (2011) Hip (hydundai integrated parking systems). Accessed 06 Dec 2016
  12. ICAM (2016) Smoov ASRV generation 2. Accessed 06 Dec 2016
  13. IFL IfFuL (2015) Gridstore. Accessed 06 Dec 2016
  14. Kim CW, Tanchoco JMA (1991) Conflict-free shortest-time bidirectional AGV routeing. Int J Prod Res 29(12):2377–2391CrossRefGoogle Scholar
  15. Kota VR, Taylor D, Gue KR (2010) Retrieval time performance in puzzle-based storage systems. In: Johnson A, Miller J (eds) Proceedings of the 2010 industrial engineering research conference (IERC)Google Scholar
  16. Kota VR, Taylor D, Gue KR (2015) Retrieval time performance in puzzle-based storage systems. J Manuf Technol Manag 26(4):582–602CrossRefGoogle Scholar
  17. Latombe JC (1991) Robot motion planning. Springer, BerlinCrossRefGoogle Scholar
  18. Mayer SH (2009) Development of a completely decentralized control system for modular continuous conveyors. Ph.D. thesis, Karlsruhe, Karlsruhe Univ, Diss, 2009.
  19. Mutrade (2014) Automatic parking system. Accessed 06 Dec 2016
  20. Nobbe C (2015) Vergleich technischer implementierungen für gridflow-systeme. Ph.D. thesisGoogle Scholar
  21. ODTH (2015) Magic black box. Accessed 06 Dec 2016
  22. Roodbergen KJ, Vis IF (2009) A survey of literature on automated storage and retrieval systems. Eur J Oper Res 194(2):343–362CrossRefGoogle Scholar
  23. RR Parkon (2014) Puzzle parking. Accessed 06 Dec 2016
  24. Schwab M (2015) A decentralized control strategy for high density material flow systems with automated guided vehicles. Ph.D. thesisGoogle Scholar
  25. Sgall J (1998) On-line scheduling. In: Fiat A, Woeginger GJ (eds) Online algorithms: the state of the art. Springer, Berlin, pp 196–231CrossRefGoogle Scholar
  26. Ter Mors AW, Witteveen C, Zutt J, Kuipers FA (2010) Context-aware route planning. In: Dix J, Witteveen C (eds) Multiagent system technologies, 8th German Conference, MATES 2010, Leipzig, Germany, vol 6251. Lecture notes in computer science. Springer, pp 138–149Google Scholar
  27. Van Den Berg JP, Gademann A (1999) Optimal routing in an automated storage/retrieval system with dedicated storage. IIE Trans 31(5):407–415CrossRefGoogle Scholar
  28. Woehr (2016) Liverpool—Parksafe 583. Accessed 06 Dec 2016
  29. Yalcin A, Koberstein A, Schocke KO (2018) An optimal and a heuristic algorithm for the single-item retrieval problem in puzzle-based storage systems with multiple escorts. Int J Prod Res.
  30. Zaerpour N, Yu Y, de Koster RBM (2015) Small is beautiful: a framework for evaluating and optimizing live-cube compact storage systems. Transp Sci.

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.European University Viadrina Frankfurt (Oder)Frankfurt (Oder)Germany
  2. 2.Frankfurt University of Applied SciencesFrankfurt (Main)Germany

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