# Estimating and Optimizing Congestion Delay in Picker-to-Part Systems

Pablo Torrealba-González, Dominique Feillet, Maxime Ogier, Frédéric Semet

► To cite this version:

Pablo Torrealba-González, Dominique Feillet, Maxime Ogier, Frédéric Semet. Estimating and Optimizing Congestion Delay in Picker-to-Part Systems. First Workshop on Warehouse Management and Logistics, Oct 2024, Lille, France. hal-04864953

HAL Id: hal-04864953

https://hal.science/hal-04864953v1

Submitted on 5 Jan 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Estimating and Optimizing Congestion Delay in
Picker-to-Part Systems

Pablo Torrealba*¹, Dominique Feillet², Maxime Ogier¹, and Frederic Semet¹

¹Centrale Lille – Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRISTAL, F-59000 Lille, France,
Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRISTAL, F-59000 Lille, France – France

²Ecole des Mines de Saint-Etienne - CMP – Mines Saint-Etienne, Univ. Clermont Auvergne, LIMOS
UMR CNRS 6158, Centre CMP, Gardanne F-13541, France – France

Abstract

In the context of warehosue operations, picker-to-part systems are operational setups
in which operators, commmonly called pickers, navigate around the warehouse collecting
all the necessary products to prepare customer orders. In the Operations Research scope,
a common assumption is to consider a complete independent operation scenario for each
 picker, neglecting potential interactions between pickers.

Nowadays, given the changes on the behavior of customers it is common to see a large number
of pickers operating simultaneously. This frame can lead to undesirable situations in which
congestion appears. Congestion occurs when two or more pickers compete for the use of a
shared space, delaying operational times and impacting overall performance.

In this work, we propose a mathematical and computational approach to estimate the delay
produced by congestion on the total operation times. We analyze the delay in terms of the
main factors and different storage policies and evaluate the effect of approximating it by
using a time discretization. Finally, we present a column generation based solving procedure
to optimize order batching and picker routing decisions, explicitly considering the impact of
congestion on the total completion times.

<footnote>*Speaker</footnote>