IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v29y2018i2d10.1007_s10845-015-1116-7.html
   My bibliography  Save this article

A Genetic Algorithm applied to pick sequencing for billing

Author

Listed:
  • Anderson Rogério Faia Pinto

    (University of São Paulo)

  • Antonio Fernando Crepaldi

    (São Paulo State University)

  • Marcelo Seido Nagano

    (University of São Paulo)

Abstract

This article addresses the use of Holland’s Genetic Algorithms (GAs) (Holland in Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, MI, 1975) in solving an optimization problem not exploited yet by literature, which we have named Optimal Billing Sequencing (OBS). The objective of the GA proposed is to automate pick sequencing, which addresses the process of allocating the stock available for sale to the purchase orders in a portfolio, so that the maximization of the billing is the optimal result for the OBS. A modelling and computational simulation methodology has been employed. Such methodology is designed to enable the GA to meet the boundary conditions established by predefined decision restrictions and parameters. We have reached the conclusion, by means of experimental tests, that the GA developed satisfactorily solves the problem studied. In addition to a low computational overhead, the GA reduces operating costs and speeds picking decision-making processes and billing processes.

Suggested Citation

  • Anderson Rogério Faia Pinto & Antonio Fernando Crepaldi & Marcelo Seido Nagano, 2018. "A Genetic Algorithm applied to pick sequencing for billing," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 405-422, February.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:2:d:10.1007_s10845-015-1116-7
    DOI: 10.1007/s10845-015-1116-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-015-1116-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-015-1116-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Haegeman, Karel & Marinelli, Elisabetta & Scapolo, Fabiana & Ricci, Andrea & Sokolov, Alexander, 2013. "Quantitative and qualitative approaches in Future-oriented Technology Analysis (FTA): From combination to integration?," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 386-397.
    2. Gu, Jinxiang & Goetschalckx, Marc & McGinnis, Leon F., 2007. "Research on warehouse operation: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 177(1), pages 1-21, February.
    3. Matthews, Jason & Visagie, Stephan, 2013. "Order sequencing on a unidirectional cyclical picking line," European Journal of Operational Research, Elsevier, vol. 231(1), pages 79-87.
    4. Slotnick, Susan A., 2011. "Order acceptance and scheduling: A taxonomy and review," European Journal of Operational Research, Elsevier, vol. 212(1), pages 1-11, July.
    5. Joshua Hallam & Olcay Akman & Füsun Akman, 2010. "Genetic algorithms with shrinking population size," Computational Statistics, Springer, vol. 25(4), pages 691-705, December.
    6. Ghiselin, Michael T., 2009. "Darwin and the evolutionary foundations of society," Journal of Economic Behavior & Organization, Elsevier, vol. 71(1), pages 4-9, July.
    7. Mehrdad Shahabi & Shirin Akbarinasaji & Avinash Unnikrishnan & Rachel James, 2013. "Integrated Inventory Control and Facility Location Decisions in a Multi-Echelon Supply Chain Network with Hubs," Networks and Spatial Economics, Springer, vol. 13(4), pages 497-514, December.
    8. Berg, J. P. van den & Zijm, W. H. M., 1999. "Models for warehouse management: Classification and examples," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 519-528, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anderson Rogério Faia Pinto & Marcelo Seido Nagano, 2020. "Genetic algorithms applied to integration and optimization of billing and picking processes," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 641-659, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Lu & Langevin, André & Riopel, Diane, 2011. "A tabu search algorithm for the relocation problem in a warehousing system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 147-156, January.
    2. Gianluca Nastasi & Valentina Colla & Silvia Cateni & Simone Campigli, 2018. "Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1545-1557, October.
    3. Michele Barbato & Alberto Ceselli & Giovanni Righini, 2024. "A polynomial-time dynamic programming algorithm for an optimal picking problem in automated warehouses," Journal of Scheduling, Springer, vol. 27(4), pages 393-407, August.
    4. Yu, Y. & de Koster, M.B.M., 2009. "On the Suboptimality of Full Turnover-Based Storage," ERIM Report Series Research in Management ERS-2009-051-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Vidal Vieira, José Geraldo & Ramos Toso, Milton & da Silva, João Eduardo Azevedo Ramos & Cabral Ribeiro, Priscilla Cristina, 2017. "An AHP-based framework for logistics operations in distribution centres," International Journal of Production Economics, Elsevier, vol. 187(C), pages 246-259.
    6. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    7. Bouzekri, Hamza & Bara, Najat & Alpan, Gülgün & Giard, Vincent, 2022. "An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain," International Journal of Production Economics, Elsevier, vol. 252(C).
    8. Lim, Ming K. & Bahr, Witold & Leung, Stephen C.H., 2013. "RFID in the warehouse: A literature analysis (1995–2010) of its applications, benefits, challenges and future trends," International Journal of Production Economics, Elsevier, vol. 145(1), pages 409-430.
    9. Mourad Makaci & Paul J. Reaidy & Karine Evrard Samuel & Valérie Botta-Genoulaz & Thibaud Monteiro, 2017. "Pooled warehouse management : An empirical study," Post-Print hal-01531304, HAL.
    10. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    11. Anderson Rogério Faia Pinto & Marcelo Seido Nagano, 2020. "Genetic algorithms applied to integration and optimization of billing and picking processes," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 641-659, March.
    12. Mofidi, Seyed Shahab & Pazour, Jennifer A. & Roy, Debjit, 2018. "Proactive vs. reactive order-fulfillment resource allocation for sea-based logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 66-84.
    13. Dario Pacciarelli & Andrea D’Ariano & Michele Scotto, 2011. "Applying RFID in warehouse operations of an Italian courier express company," Netnomics, Springer, vol. 12(3), pages 209-222, October.
    14. Wang, Xiuli & Cheng, T.C.E., 2015. "A heuristic for scheduling jobs on two identical parallel machines with a machine availability constraint," International Journal of Production Economics, Elsevier, vol. 161(C), pages 74-82.
    15. Havas, Attila & Weber, K. Matthias, 2017. "The 'fit' between forward-looking activities and the innovation policy governance sub-system: A framework to explore potential impacts," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 327-337.
    16. Sokolov, Alexander & Shashnov, Sergey & Kotsemir, Maxim & Grebenyuk, Anna, 2019. "Quantitative analysis for a better-focused international STI collaboration policy: A case of BRICS," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 221-242.
    17. Thierry Sauvage & Tony Cragg & Sarrah Chraibi & Oussama El Khalil Houssaini, 2018. "Running the Machine Faster: Acceleration, Humans and Warehousing," Post-Print hal-02905068, HAL.
    18. Wang, Xiuli & Zhu, Qianqian & Cheng, T.C.E., 2015. "Subcontracting price schemes for order acceptance and scheduling," Omega, Elsevier, vol. 54(C), pages 1-10.
    19. Jone R. Hansen & Kjetil Fagerholt & Magnus Stålhane & Jørgen G. Rakke, 2020. "An adaptive large neighborhood search heuristic for the planar storage location assignment problem: application to stowage planning for Roll-on Roll-off ships," Journal of Heuristics, Springer, vol. 26(6), pages 885-912, December.
    20. K. H. Chow & K. L. Choy & W. B. Lee, 2006. "On the design of a real‐time knowledge‐based system for managing logistics operations," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 14(1‐2), pages 3-25, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:29:y:2018:i:2:d:10.1007_s10845-015-1116-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.