Skip to main content
Log in

Design of diagonal cross-aisle warehouses with class-based storage assignment strategy

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Non-traditional warehouses shorten the travelled paths to store and retrieve (S/R) the loads, thanks to additional aisles crossing the parallel racks. This paper provides the analytic model to best design a non-traditional warehouse for unit-load (UL) with diagonal cross-aisles and storage policy according to the class-based storage (CBS) strategy. The model minimizes the average single-command cycle time to S/R the loads, best sizing the classes, their shape, and the position/numbers of additional aisles. The focus is on both 2- and 3-CBS optimizing the number of diagonal cross-aisles to best balance the travel time reduction and the loss of storage space due to the aisles. Furthermore, benchmarking toward standard warehouses with no diagonal cross-aisles and random assignment strategy allows quantifying the positive impact of the proposed design configuration on the daily warehouse operations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Horta M, Coelho F, Relvas S (2016) Layout design modelling for a real world just-in-time warehouse. Comput Ind Eng 101:1–9

    Article  Google Scholar 

  2. Zhang G, Nishi T, Turner SDO, Oga K, Li X (2017) An integrated strategy for a production planning and warehouse layout problem: modeling and solution approaches. Omega 68:85–94

    Article  Google Scholar 

  3. Boysen N, de Koster R, Weidinger F (2018) Warehousing in the e-commerce era: a survey. Eur J Oper Res

  4. Gu J, Goetschalckx M, McGinnis L (2007) Research on warehouse operation: a comprehensive review. Eur J Oper Res 177(1):1–21

    Article  MATH  Google Scholar 

  5. Rouwenhorst B, Reuter B, Stockrahm V, van Houtum G, Mantel R, Zijm W (2000) Warehouse design and control: framework and literature review. Eur J Oper Res 122:515–533

    Article  MATH  Google Scholar 

  6. Baker P, Canessa M (2009) Warehouse design: a structured approach. Eur J Oper Res 193:425–436

    Article  Google Scholar 

  7. Gu J, Goetschalckx M, McGinnis L (2010) Research on warehouse design and performance evaluation: a comprehensive review. Eur J Oper Res 203(3):539–549

    Article  MATH  Google Scholar 

  8. Cormier G, Gunn EA (1992) A review of warehouse models. Eur J Oper Res 58:3–13

    Article  Google Scholar 

  9. Accorsi R, Bortolini M, Gamberi M, Manzini R, Pilati F (2017) Multi-objective warehouse building design to optimize the cycle time, total cost, and carbon footprint. Int J Adv Manuf Technol 92(1–4):839–854

    Article  Google Scholar 

  10. Staudt FH, Alpan G, Di Mascolo M, Taboada Rodriguez CM (2015) Warehouse performance assessment: a literature review. Int J Prod Res 53(18):5524–5544

    Article  Google Scholar 

  11. Dotoli M, Epicoco N, Falagario M, Costantino N, Turchiano B (2015) An integrated approach for warehouse analysis and optimization: a case study. Comput Ind 70:56–69

    Article  Google Scholar 

  12. Gue KR, Meller RD (2009) Aisle configurations for unit-load warehouses. IIE Trans 41(3):171–182

    Article  Google Scholar 

  13. De Koster R, Le-Duc T, Roodbergen KJ (2007) Design and control of warehouse order picking: a literature review. Eur J Oper Res 182:481–501

    Article  MATH  Google Scholar 

  14. Bartholdi JJ, Hackman ST (2017) Warehouse and distribution science, version 0.98. https://www.warehouse-science.com/book/editions/wh-sci-0.98.pdf. Accessed 5 February 2018

  15. Roodbergen KJ, De Koster R (2001) Routing order pickers in a warehouse with a middle aisle. Eur J Oper Res 133:32–43

    Article  MathSciNet  MATH  Google Scholar 

  16. Accorsi R, Manzini R, Maranesi F (2014) A decision-support system for the design and management of warehousing systems. Comput Ind 65:175–186

    Article  Google Scholar 

  17. Öztürkoglu O, Gue KR, Meller RD (2012) Optimal unit-load warehouse designs for single-command operations. IIE Trans 44:459–475

    Article  Google Scholar 

  18. Le-Duc T, De Koster R (2005) Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse. Int J Prod Res 43(17):3561–3581

    Article  MATH  Google Scholar 

  19. Hausman WH, Schwarz LB, Graves SC (1976) Optimal storage assignment in automatic warehousing systems. Manag Sci 22(6):629–638

    Article  MATH  Google Scholar 

  20. Bortolini M, Accorsi R, Gamberi M, Manzini R, Regattieri A (2015) Optimal design of AS/RS storage systems with three-class-based assignment strategy under single and dual command operations. Int J Adv Manuf Technol 79(9–12):1747–1759

    Article  Google Scholar 

  21. Zaerpour N, Yu Y, de Koster RBM (2017) Optimal two-class-based storage in a live-cube compact storage system. IISE Trans 49(7):653–668

    Article  Google Scholar 

  22. Bortolini M, Faccio M, Gamberi M, Manzini R (2015) Diagonal cross-aisle in unit-load warehouses to increase handling performance. Int J Prod Econ 170:838–849

    Article  Google Scholar 

  23. Gabbard M, Reinholdt E (1975) Warehouse cost analysis. West Electr Eng 19:52–60

    Google Scholar 

  24. Rai D, Sodegar B, Fieldson R, Hu X (2011) Assessment of CO2 emissions reduction in a distribution warehouse. Energy 36:2271–2277

    Article  Google Scholar 

  25. Chew EP, Tang LC (1999) Cycle time analysis for general item location assignment in a rectangular warehouse. Eur J Oper Res 112:582–597

    Article  MATH  Google Scholar 

  26. Wang G, Feng G, Kang Z, Wang H (2017) Research on the heat load of food freezing in refrigerated warehouse. Procedia Eng 205:1843–1849

    Article  Google Scholar 

  27. Bortolini M, Faccio M, Ferrari E, Gamberi M, Pilati F (2016) Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization. J Food Eng 174:56–67

    Article  Google Scholar 

  28. Ding B (2018) Pharma Industry 4.0: literature review and research opportunities in sustainable pharmaceutical supply chains. Process Saf Environ Prot 119:115–130

    Article  Google Scholar 

  29. Liu X, Li J, Li X (2017) Study of dynamic risk management system for flammable and explosive dangerous chemicals storage area. J Loss Prev Process Ind 49:983–988

    Article  Google Scholar 

  30. Khakzad N, Van Gelder P (2017) Fragility assessment of chemical storage tanks subject to floods. Process Saf Environ Prot 111:75–84

    Article  Google Scholar 

  31. Bassan Y, Roll Y, Rosenblatt MJ (1980) Internal layout design of a warehouse. IIE Trans 12(4):317–322

    Google Scholar 

  32. White J (1972) Optimum design of warehouses having radial aisles. AIIE Trans 4(4):333–336

    Article  Google Scholar 

  33. Arlinghaus SL, Nystuen JD (1991) Street geometry and flows. Geogr Rev 81(2):206–214

    Article  Google Scholar 

  34. Clark KA, Meller RD (2013) Incorporating vertical travel into non-traditional cross-aisles for unit-load warehouse designs. IIE Trans 45(12):1322–1331

    Article  Google Scholar 

  35. Cardona LF, Soto DF, Rivera L, Martínez HJ (2015) Detailed design of fishbone warehouse layouts with vertical travel. Int J Prod Econ 170:825–837

    Article  Google Scholar 

  36. Çelk M, Süral H (2014) Order picking under random and turnover-based storage policies in fishbone aisle warehouses. IIE Trans 46(3):283–300

    Article  Google Scholar 

  37. Pohl LM, Meller RD, Gue KR (2009) An analysis of dual-command operations in common warehouse designs. Transport Res E-Log 45(3):367–379

    Article  Google Scholar 

  38. Pohl LM, Meller RD, Gue KR (2009) Optimizing fishbone aisles for dual-command operations in a warehouse. Nav Res Logist 56(5):389–403

    Article  MathSciNet  MATH  Google Scholar 

  39. Gue KR, Ivanovic G, Meller RD (2012) A unit-load warehouse with multiple pickup and deposit points and non-traditional aisles. Transp Res E 48(4):795–806

    Article  Google Scholar 

  40. Thomas LM, Meller RD (2014) Analytical models for warehouse configuration. IIE Trans 46(9):928–947

    Article  Google Scholar 

  41. Pferschy U, Schauer J (2018) Order batching and routing in a non-standard warehouse. Electron Notes Discrete Math 69:125–132

    Article  MathSciNet  Google Scholar 

  42. Heskett J (1963) Cube-per-order index: a key to warehouse stock location. Transp Distrib Manag 3:27–31

    Google Scholar 

  43. Kallina C, Lynn J (1976) Application of the cube-per-order index rule for stock location in a distribution warehouse. Interfaces 7:37–46

    Article  Google Scholar 

  44. Manzini R, Gamberi M, Persona A, Regattieri A (2007) Design of a class based storage picker to product order picking system. Int J Adv Manuf Technol 32(7–8):811–821

    Article  Google Scholar 

  45. Larson TN, March H, Kusiak A (1997) Heuristic approach to warehouse layout with class-based storage. IIE Trans 29(4):337–348

    Google Scholar 

  46. Kovács A (2011) Optimizing the storage assignment in a warehouse served by milkrun logistics. Int J Prod Econ 133(1):312–318

    Article  Google Scholar 

  47. Ene S, Öztürk N (2012) Storage location assignment and order picking optimization in the automotive industry. Int J Adv Manuf Technol 60(5–8):787–797

    Article  Google Scholar 

  48. Rao SS, Adil GK (2013) Class-based storage with exact S-shaped traversal routing in low-level picker-to-part systems. Int J Prod Res 51(16):4979–4996

    Article  Google Scholar 

  49. Yu Y, De Koster R (2013) On the suboptimality of full turnover-based storage. Int J Prod Res 51(6):1635–1647

    Article  Google Scholar 

  50. Ekren BY, Sari Z, Lerher T (2015) Warehouse design under class-based storage policy of shuttle-based storage and retrieval system. IFAC Pap Online 48(3):1152–1154

    Article  Google Scholar 

  51. Flores B, Whybark C (1986) Multiple criteria ABC analysis. Int J Oper Prod Manag 6:38–46

    Article  Google Scholar 

  52. Lolli F, Ishizaka A, Gamberini R, Rimini B (2017) A multicriteria framework for inventory classification and control with application to intermitted demand. J Multi-Criteria Decis Anal 24:275–285

    Article  Google Scholar 

  53. Lolli F, Ishizaka A, Gamberini R (2014) New AHP-based approaches for multi-criteria inventory classification. Int J Prod Econ 156:62–74

    Article  Google Scholar 

  54. Ishizaka A, Lolli F, Balugani E, Cavallieri R, Gamberini R (2018) DEASort: assigning items with data envelopment analysis in ABC classes. Int J Prod Econ 199:7–15

    Article  Google Scholar 

  55. Soylu B, Akyol B (2014) Multi-criteria inventory classification with reference items. Comput Ind Eng 69:12–20

    Article  Google Scholar 

  56. Douissa MR, Jabeur K (2016) A new model for multi-criteria ABC inventory classification: PROAFTN method. Procedia Comput Sci 96:550–559

    Article  Google Scholar 

  57. Torabi SA, Hatefi SM, Salek Pay B (2012) ABC inventory classification in the presence of both quantitative and qualitative criteria. Comput Ind Eng 63:530–537

    Article  Google Scholar 

  58. Bonnans JF, Gilbert JC, Lemaréchal C, Sagastizábal CA (2006) Numerical optimization: theoretical and practical aspects. Universitext (Second revised ed. of translation of 1997 French ed.) Springer-Verlag, Berlin

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marco Bortolini.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bortolini, M., Faccio, M., Ferrari, E. et al. Design of diagonal cross-aisle warehouses with class-based storage assignment strategy. Int J Adv Manuf Technol 100, 2521–2536 (2019). https://doi.org/10.1007/s00170-018-2833-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-018-2833-9

Keywords

Navigation