The price of safety: Order picking in warehouses with in-house traffic regulations

Blue-collar work in warehouses is prone to occupational accidents, especially in large distribution centers where motorized traffic of forklifts, picking carts, and AGVs interfere with human pickers.To improve the safety of these work environments, many warehouses apply specific in-house traffic regulations.Prominent prohibitions include banning U-turns within aisles and left-turns at intersections.Further safety measures are one-way aisles and dedicated traffic lanes prohibiting picks from racks across the oncoming traffic.On the negative side of the safety-performance trade-off, these safety measures reduce routing flexibility and prolong picking tours.We explore the price of safety by integrating different in-house traffic regulations into an exact picker routing algorithm that finds optimal routes within multi-cross-aisle warehouses in polynomial time.We use state-ofthe-art TSP solvers for safety measures where this is impossible.Our investigation enables managers to choose the right combination of traffic regulations to improve safety without increasing the picking tour length too much.Our computational results show that a fit of warehouse layout and safety measures is crucial, as they increase the optimal picker tours without restrictions between 3 and 139% on average.

Authors

Institutions

Publication Details

Journal
IISE Transactions
Published
2024-12-04
DOI
https://doi.org/10.1080/24725854.2024.2434922
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The price of safety: Order picking in warehouses with in-house traffic regulations

Tobias Kroll, Nils Boysen, Stefan Bock, Rebecca Braken
IISE Transactions
Advanced Manufacturing and Logistics Optimization
article

The price of safety: Order picking in warehouses with in-house traffic regulations

Tobias Kroll, Nils Boysen, Stefan Bock, Rebecca Braken
article en

Abstract

Blue-collar work in warehouses is prone to occupational accidents, especially in large distribution centers where motorized traffic of forklifts, picking carts, and AGVs interfere with human pickers.To improve the safety of these work environments, many warehouses apply specific in-house traffic regulations.Prominent prohibitions include banning U-turns within aisles and left-turns at intersections.Further safety measures are one-way aisles and dedicated traffic lanes prohibiting picks from racks across the oncoming traffic.On the negative side of the safety-performance trade-off, these safety measures reduce routing flexibility and prolong picking tours.We explore the price of safety by integrating different in-house traffic regulations into an exact picker routing algorithm that finds optimal routes within multi-cross-aisle warehouses in polynomial time.We use state-ofthe-art TSP solvers for safety measures where this is impossible.Our investigation enables managers to choose the right combination of traffic regulations to improve safety without increasing the picking tour length too much.Our computational results show that a fit of warehouse layout and safety measures is crucial, as they increase the optimal picker tours without restrictions between 3 and 139% on average.

IISE TransactionsVol. 57(10)
University of Wuppertal (DE), Schiller International University (FR), Friedrich Schiller University Jena (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 68%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.