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Optimization of a Rectangular Warehouse Design Using Heuristics Techniques

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Resumen

This research aims to determine the number of cross aisles that minimizes distance traveled. To achieve this, a rectangular warehouse with various transverse aisles was defined, and simulations were conducted with 0 to 90 transverse aisles using heuristic algorithms (FCFS, G01, G02, G03, RANDOM, and SOP) for order batching, and S-Shape and L-Gap for order picking. The simulations considered a list of 20 to 100 orders or carts with a capacity of 30 to 75 order items. As a result, ANOVA analysis demonstrates the significance of order batching and picking algorithms, number of orders and cart capacity. The order batching algorithms that provide minimum distances in these experiments are G03 and RANDOM, and for order picking, LGAP algorithm is most effective. The number of cross aisles in configuration presented in this research that yields the minimum distances is 26; however, this is not conclusive to ensure that minimum distances will always be achieved with this number of transverse aisles.

Idioma originalInglés
Título de la publicación alojadaSystems, Smart Technologies, and Innovation for Society - Proceedings of CITIS 2024
EditoresEsteban Mauricio Inga Ortega, Vladimir Espartaco Robles-Bykbaev, Nuria García Herranz, Eduardo Gallego Diaz
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas93-104
Número de páginas12
ISBN (versión impresa)9783031870644
DOI
EstadoPublicada - 2025
Evento10th International Conference on Science, Technology and Innovation for Society, CITIS 2024 - Guayaquil, Ecuador
Duración: 18 jul. 202419 jul. 2024

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen1331 LNNS
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389

Conferencia

Conferencia10th International Conference on Science, Technology and Innovation for Society, CITIS 2024
País/TerritorioEcuador
CiudadGuayaquil
Período18/07/2419/07/24

Nota bibliográfica

Publisher Copyright:
© The Author(s) 2025.

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