Improving warehouse operations: leveraging simulation for efficient layout design and process improvement in a picking by line operation

This study focuses on improving the picking processes within a Picking-by-Line (PBL) warehouse through the development of a simulation model to assess different layouts and new operational rules. Utilizing a combination of Discrete Event Simulation (DES) and Agent-Based Modeling (ABS) in AnyLogic, the simulation model was validated against real-world Key Performance Indicators (KPIs) to ensure accuracy. The study identified three primary improvement opportunities. To address these opportunities, four scenarios were tested. The results showed varying impacts on productivity, with three of the four scenarios yielding improvements in picking productivity. Pilot testing confirmed the simulation model’s predictions. The findings indicate that balancing travel distance reduction with congestion management is key to increasing picking productivity. This study reaffirms the value of simulation modeling in warehouse management, providing a robust framework for free-risk testing.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.07.058
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Improving warehouse operations: leveraging simulation for efficient layout design and process improvement in a picking by line operation

Maria Sameiro Carvalho, Elsa Silva, Miguel de Carvalho Paula
Procedia Computer Science
Advanced Manufacturing and Logistics Optimization
article

Improving warehouse operations: leveraging simulation for efficient layout design and process improvement in a picking by line operation

Maria Sameiro Carvalho, Elsa Silva, Miguel de Carvalho Paula
article en

Abstract

This study focuses on improving the picking processes within a Picking-by-Line (PBL) warehouse through the development of a simulation model to assess different layouts and new operational rules. Utilizing a combination of Discrete Event Simulation (DES) and Agent-Based Modeling (ABS) in AnyLogic, the simulation model was validated against real-world Key Performance Indicators (KPIs) to ensure accuracy. The study identified three primary improvement opportunities. To address these opportunities, four scenarios were tested. The results showed varying impacts on productivity, with three of the four scenarios yielding improvements in picking productivity. Pilot testing confirmed the simulation model’s predictions. The findings indicate that balancing travel distance reduction with congestion management is key to increasing picking productivity. This study reaffirms the value of simulation modeling in warehouse management, providing a robust framework for free-risk testing.

Procedia Computer ScienceVol. 263
University of Minho (PT)
Openalex Percentile: Top 71%
Advanced Manufacturing and Logistics Optimization
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