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

  • Jose Alejandro CanoEmail author
  • Alexander Alberto Correa-Espinal
  • Rodrigo Andrés Gómez-Montoya
  • Pablo Cortés
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)

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.

Keywords

Order picking Picker routing Genetic algorithm Artificial intelligence Multi-block warehouse Warehouse management 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidad de MedellínMedellínColombia
  2. 2.Universidad Nacional de ColombiaMedellínColombia
  3. 3.ESACS – Escuela Superior en Administración de Cadena de SuministroMedellínColombia
  4. 4.Universidad de SevillaSevillaSpain

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