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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
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    References listed on IDEAS

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    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.

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