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Evaluating Order Picking Efficiency Under Demand Fluctuations

  • Jens BürgerEmail author
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

Storage location assignment is a dynamic problem due to product life cycles and time-varying demand patterns. We demonstrate the impact of demand fluctuations on order picking times for frequency-based and genetic-algorithm-based storage assignment policies. Our results provide the base for developing re-warehousing strategies to maintain order picking efficiency over time.

Keywords

Order picking Storage location assignment problem Genetic algorithm 

References

  1. 1.
    Bassan, Y., Roll, Y., Rosenblatt, M.J.: Internal layout design of a warehouse. AIIE Trans. 12(4), 317–322 (1980)CrossRefGoogle Scholar
  2. 2.
    Brynzér, H., Johansson, M.I.: Storage location assignment: using the product structure to reduce order picking times. Int. J. Prod. Econ. 46, 595–603 (1996)CrossRefGoogle Scholar
  3. 3.
    Coyle, J.J., Bardi, E.J., Langley, C.J.: The Management of Business Logistics, vol. 6. West Publishing Company, St. Paul (1996)Google Scholar
  4. 4.
    De Koster, R., Le-Duc, T., Roodbergen, K.J.: Design and control of warehouse order picking: a literature review. Eur. J. Oper. Res. 182(2), 481–501 (2007)CrossRefGoogle Scholar
  5. 5.
    Fortin, F.-A., Rainville, F.-M.D., Gardner, M.-A., Parizeau, M., Gagné, C.: DEAP: evolutionary algorithms made easy. J. Mach. Learn. Res. 13, 2171–2175 (2012)Google Scholar
  6. 6.
    Gademann, N., Velde, S.: Order batching to minimize total travel time in a parallel-aisle warehouse. IIE Trans. 37(1), 63–75 (2005)CrossRefGoogle Scholar
  7. 7.
    Hall, R.W.: Distance approximations for routing manual pickers in a warehouse. IIE Trans. 25(4), 76–87 (1993)CrossRefGoogle Scholar
  8. 8.
    Kofler, M., Beham, A., Wagner, S., Affenzeller, M.: Robust storage assignment in warehouses with correlated demand. In: Computational Intelligence and Efficiency in Engineering Systems, pp. 415–428. Springer (2015)Google Scholar
  9. 9.
    Kofler, M., Beham, A., Wagner, S., Affenzeller, M., Achleitner, W.: Re-warehousing vs. healing: strategies for warehouse storage location assignment. In: 2011 3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI), pp. 77–82. IEEE (2011)Google Scholar
  10. 10.
    Laporte, G.: The traveling salesman problem: an overview of exact and approximate algorithms. Eur. J. Oper. Res. 59(2), 231–247 (1992)CrossRefGoogle Scholar
  11. 11.
    Lu, W., McFarlane, D., Giannikas, V., Zhang, Q.: An algorithm for dynamic order-picking in warehouse operations. Eur. J. Oper. Res. 248(1), 107–122 (2016)CrossRefGoogle Scholar
  12. 12.
    Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press (1998)Google Scholar
  13. 13.
    Quintanilla, S., Pérez, Á., Ballestín, F., Lino, P.: Heuristic algorithms for a storage location assignment problem in a chaotic warehouse. Eng. Optim. 47(10), 1405–1422 (2015)CrossRefGoogle Scholar
  14. 14.
    Roodbergen, K.J., Koster, R.d.: Routing methods for warehouses with multiple cross aisles. Int. J. Prod. Res. 39(9), 1865–1883 (2001)Google Scholar
  15. 15.
    Tompkins, J.A., White, J.A., Bozer, Y.A., Tanchoco, J.M.A.: Facilities Planning. Wiley (2010)Google Scholar
  16. 16.
    Zhao, F.: Forecasts for product demand. https://www.kaggle.com/felixzhao/productdemandforecasting/home (1998). Version 1. Accessed 20 Sept 2018

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Centro de Investigaciones en Nuevas Tecnologías InformáticasUniversidad Privada BolivianaCochabambaBolivia
  2. 2.Institute for Computational IntelligenceUniversidad Privada BolivianaCochabambaBolivia

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