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Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses

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Business Information Systems (BIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 353))

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Abstract

This article presents a genetic algorithm (GA) to solve the picker routing problem in multiple-block warehouses in order to minimize the traveled distance. The GA uses survival, crossover, immigration, and mutation operators, and is complemented by a local search heuristic. The genetic algorithm provides average distance savings of 13.9% when compared with s-shape strategy, and distance savings of 23.3% when compared with the GA with the aisle-by-aisle policy. We concluded that the GA performs better as the number of blocks increases, and as the percentage of picking locations to visit decreases.

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Author information

Authors and Affiliations

  1. Universidad de Medellín, Carrera 87 # 30-65, Medellín, Colombia

    Jose Alejandro Cano

  2. Universidad Nacional de Colombia, Carrera 80 # 65-223, Medellín, Colombia

    Alexander Alberto Correa-Espinal

  3. ESACS – Escuela Superior en Administración de Cadena de Suministro, Calle 4 # 18-55, Medellín, Colombia

    Rodrigo Andrés Gómez-Montoya

  4. Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092, Sevilla, Spain

    Pablo Cortés

Authors
  1. Jose Alejandro Cano
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  2. Alexander Alberto Correa-Espinal
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  3. Rodrigo Andrés Gómez-Montoya
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  4. Pablo Cortés
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Corresponding author

Correspondence to Jose Alejandro Cano .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Witold Abramowicz

  2. ETSI Informática, University of Seville, Seville, Spain

    Rafael Corchuelo

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Cano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., Cortés, P. (2019). Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems. BIS 2019. Lecture Notes in Business Information Processing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-030-20485-3_24

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  • DOI: https://doi.org/10.1007/978-3-030-20485-3_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20484-6

  • Online ISBN: 978-3-030-20485-3

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