scholarly journals Improving Order Picking Efficiency by Analyzing Combinations of Storage, Batching, Zoning, and Routing Policies

2016 ◽  
pp. 427-442 ◽  
Author(s):  
Teun van Gils ◽  
Kris Braekers ◽  
Katrien Ramaekers ◽  
Benoît Depaire ◽  
An Caris
Keyword(s):  
Order Picking ◽  
Routing Policies

A comparison of picking, storage, and routing policies in manual order picking

2004 ◽  
Vol 92 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Charles G. Petersen ◽  
Gerald Aase
Keyword(s):  
Order Picking ◽  
Routing Policies

An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses

2017 ◽  
Vol 28 (3) ◽  
pp. 841-863 ◽  
Author(s):  
Torsten Franzke ◽  
Eric H. Grosse ◽  
Christoph H. Glock ◽  
Ralf Elbert
Keyword(s):  
Simulation Model ◽  
Order Picking ◽  
Content Type ◽  
Agent Based ◽  
Routing Policy ◽  
Storage Assignment ◽  
Alternative Routing ◽  
Routing Policies ◽  
The Individual ◽  
Picker Blocking

Purpose Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in recent years. One potential source for improving order picking is the reduction of picker blocking. The purpose of this paper is to investigate picker blocking under different storage assignment and order picker-route combinations and evaluate its effects on the performance of manual order picking processes. Design/methodology/approach This study develops an agent-based simulation model (ABS) for order picking in a rectangular warehouse. By employing an ABS, we are able to study the behaviour of individual order pickers and their interactions with the environment. Findings The simulation model determines shortest mean throughput times when the same routing policy is assigned to all order pickers. In addition, it evaluates the efficiency of alternative routing policies–storage assignment combinations. Research limitations/implications The paper implies that ABS is well-suited for further investigations in the field of picker blocking, for example, with respect to the individual behaviour of agents. Practical implications Based on the results of this paper, warehouse managers can choose an appropriate routing policy that best matches their storage assignment policy and the number of order pickers employed. Originality/value This paper is the first to comprehensively study the effects of different combinations of order picker routing and storage assignment policies on the occurrence of picker blocking.

The effects of human behavior on the efficiency of routing policies in order picking: The case of route deviations

2017 ◽  
Vol 111 ◽  
pp. 537-551 ◽  
Author(s):  
Ralf M. Elbert ◽  
Torsten Franzke ◽  
Christoph H. Glock ◽  
Eric H. Grosse
Keyword(s):  
Human Behavior ◽  
Order Picking ◽  
Routing Policies

Order Picking Optimization Based on a Picker Routing Heuristic

2020 ◽  
pp. 74-96
Author(s):  
Jose Alejandro Cano
Keyword(s):  
Performance Evaluation ◽  
Numerical Experiments ◽  
Efficient Solution ◽  
Heuristic Method ◽  
Order Picking ◽  
Travel Distance ◽  
Routing Problem ◽  
Routing Policies

This chapter details the performance evaluation of routing policies and proposes a routing heuristic to determine the minimum traveled distance for different warehouse configurations and pick-list sizes. Numerical experiments are performed considering warehouse configurations used in literature and list sizes are chosen proportional to the number of storage positions of each layout. The proposed heuristic method was shown to reduce the distance traveled by 7% for the evaluated instances. Furthermore, travel distance reductions of up to 30% were found in cases involving large warehouse and pick-list sizes. The proposed heuristic therefore is concluded to provide a more efficient solution than individual routing policies for the picker routing problem.

scholarly journals Towards a conceptualisation of Order Picking 4.0

2021 ◽  
pp. 107511
Author(s):  
Sven Winkelhaus ◽  
Eric H. Grosse ◽  
Stefan Morana
Keyword(s):  
Order Picking

See the light: Optimization of put‐to‐light order picking systems

2020 ◽  
Vol 67 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Nils Boysen ◽  
David Füßler ◽  
Konrad Stephan
Keyword(s):  
Order Picking ◽  
Picking Systems

Load-Optimization in Reconfigurable Networks

2021 ◽  
Vol 48 (3) ◽  
pp. 39-44 ◽  
Author(s):  
Wenkai Dai ◽  
Klaus-Tycho Foerster ◽  
David Fuchssteiner ◽  
Stefan Schmid
Keyword(s):  
Data Centers ◽  
Algorithmic Problem ◽  
Reconfigurable Networks ◽  
Load Optimization ◽  
Clos Networks ◽  
Optical Circuit ◽  
Tree Topologies ◽  
Packet Switch ◽  
Routing Policies

Emerging reconfigurable data centers introduce the unprecedented flexibility in how the physical layer can be programmed to adapt to current traffic demands. These reconfigurable topologies are commonly hybrid, consisting of static and reconfigurable links, enabled by e.g. an Optical Circuit Switch (OCS) connected to top-of-rack switches in Clos networks. Even though prior work has showcased the practical benefits of hybrid networks, several crucial performance aspects are not well understood. In this paper, we study the algorithmic problem of how to jointly optimize topology and routing in reconfigurable data centers with a known traffic matrix, in order to optimize a most fundamental metric, maximum link load. We chart the corresponding algorithmic landscape by investigating both un-/splittable flows and (non-)segregated routing policies. We moreover prove that the problem is not submodular for all these routing policies, even in multi-layer trees, where a topological complexity classification of the problem reveals that already trees of depth two are intractable. However, networks that can be abstracted by a single packet switch (e.g., nonblocking Fat-Tree topologies) can be optimized efficiently, and we present optimal polynomialtime algorithms accordingly. We complement our theoretical results with trace-driven simulation studies, where our algorithms can significantly improve the network load in comparison to the state of the art.

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