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

Jose Alejandro Cano, Alexander Alberto Correa-Espinal, Rodrigo Andrés Gómez-Montoya, Pablo Cortés

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationBusiness Information Systems - 22nd International Conference, BIS 2019, Proceedings
EditorsRafael Corchuelo, Witold Abramowicz
PublisherSpringer Verlag
Pages313-322
Number of pages10
ISBN (Print)9783030204846
DOIs
StatePublished - 1 Jan 2019
Event22nd International Conference on Business Information Systems, BIS 2019 - Seville, Spain
Duration: 26 Jun 201928 Jun 2019

Publication series

NameLecture Notes in Business Information Processing
Volume353
ISSN (Print)1865-1348

Conference

Conference22nd International Conference on Business Information Systems, BIS 2019
Country/TerritorySpain
CitySeville
Period26/06/1928/06/19

Keywords

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

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