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

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

doi:10.1007/978-3-030-20485-3_24

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

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

Organizational Culture and Management Research Group

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 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 language	English
Title of host publication	Business Information Systems - 22nd International Conference, BIS 2019, Proceedings
Editors	Rafael Corchuelo, Witold Abramowicz
Publisher	Springer Verlag
Pages	313-322
Number of pages	10
ISBN (Print)	9783030204846
DOIs	https://doi.org/10.1007/978-3-030-20485-3_24
State	Published - 1 Jan 2019
Event	22nd International Conference on Business Information Systems, BIS 2019 - Seville, Spain Duration: 26 Jun 2019 → 28 Jun 2019

Publication series

Name	Lecture Notes in Business Information Processing
Volume	353
ISSN (Print)	1865-1348

Conference

Conference	22nd International Conference on Business Information Systems, BIS 2019
Country/Territory	Spain
City	Seville
Period	26/06/19 → 28/06/19

Keywords

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

Product types of Minciencias

B article - Q3

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-20485-3_24

Cite this

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 R. Corchuelo, & W. Abramowicz (Eds.), Business Information Systems - 22nd International Conference, BIS 2019, Proceedings (pp. 313-322). (Lecture Notes in Business Information Processing; Vol. 353). Springer Verlag. https://doi.org/10.1007/978-3-030-20485-3_24

Cano, Jose Alejandro ; Correa-Espinal, Alexander Alberto ; Gómez-Montoya, Rodrigo Andrés et al. / Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses. Business Information Systems - 22nd International Conference, BIS 2019, Proceedings. editor / Rafael Corchuelo ; Witold Abramowicz. Springer Verlag, 2019. pp. 313-322 (Lecture Notes in Business Information Processing).

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title = "Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses",

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

author = "Cano, {Jose Alejandro} and Correa-Espinal, {Alexander Alberto} and G{\'o}mez-Montoya, {Rodrigo Andr{\'e}s} and Pablo Cort{\'e}s",

year = "2019",

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Cano, JA, Correa-Espinal, AA, Gómez-Montoya, RA & Cortés, P 2019, Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses. in R Corchuelo & W Abramowicz (eds), Business Information Systems - 22nd International Conference, BIS 2019, Proceedings. Lecture Notes in Business Information Processing, vol. 353, Springer Verlag, pp. 313-322, 22nd International Conference on Business Information Systems, BIS 2019, Seville, Spain, 26/06/19. https://doi.org/10.1007/978-3-030-20485-3_24

Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses. / Cano, Jose Alejandro; Correa-Espinal, Alexander Alberto; Gómez-Montoya, Rodrigo Andrés et al.
Business Information Systems - 22nd International Conference, BIS 2019, Proceedings. ed. / Rafael Corchuelo; Witold Abramowicz. Springer Verlag, 2019. p. 313-322 (Lecture Notes in Business Information Processing; Vol. 353).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses

AU - Cano, Jose Alejandro

AU - Correa-Espinal, Alexander Alberto

AU - Gómez-Montoya, Rodrigo Andrés

AU - Cortés, Pablo

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Artificial intelligence

KW - Genetic algorithm

KW - Multi-block warehouse

KW - Order picking

KW - Picker routing

KW - Warehouse management

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U2 - 10.1007/978-3-030-20485-3_24

DO - 10.1007/978-3-030-20485-3_24

M3 - Contribución a la conferencia

AN - SCOPUS:85068139598

SN - 9783030204846

T3 - Lecture Notes in Business Information Processing

SP - 313

EP - 322

BT - Business Information Systems - 22nd International Conference, BIS 2019, Proceedings

A2 - Corchuelo, Rafael

A2 - Abramowicz, Witold

PB - Springer Verlag

T2 - 22nd International Conference on Business Information Systems, BIS 2019

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ER -

Cano JA, Correa-Espinal AA, Gómez-Montoya RA, Cortés P. Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses. In Corchuelo R, Abramowicz W, editors, Business Information Systems - 22nd International Conference, BIS 2019, Proceedings. Springer Verlag. 2019. p. 313-322. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-030-20485-3_24

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

Abstract

Publication series

Conference

Keywords

Product types of Minciencias

UN SDGs

Access to Document

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