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Article
Publication date: 14 August 2017

Torsten Franzke, Eric H. Grosse, Christoph H. Glock and Ralf Elbert

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…

Abstract

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.

Details

The International Journal of Logistics Management, vol. 28 no. 3
Type: Research Article
ISSN: 0957-4093

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Article
Publication date: 1 October 2005

Charles G. Petersen, Charles Siu and Daniel R. Heiser

PurposeWith the current interest in all aspects of supply chain management, the demands on warehousing have changed significantly within the past few years. In an attempt…

Abstract

PurposeWith the current interest in all aspects of supply chain management, the demands on warehousing have changed significantly within the past few years. In an attempt to meet this challenge, warehouses have become more concerned with proper slotting and storage techniques. This paper seeks to evaluate slotting measures and storage assignment strategies in a simulated manual bin‐shelving (low level picker‐to‐part) warehouse in terms of travel distance and the fulfillment time to complete an order.Design/methodology/approachThe approach utilises Monte Carlo simulation of a manual bin‐shelving pick area.FindingsThe results illustrate that popularity, turnover, and cube‐per‐order index (COI) performed best among slotting measures. Several new storage assignment strategies utilizing the concept of “golden zone” picking, which slots high demand stock‐keeping units (SKUs) at the height between the picker's waist and shoulders, were introduced. Results from the simulation study show that the golden zone storage assignment strategies generated significant savings in order fulfillment time compared to storage policies that ignore the golden zone concept.Originality/valueProvides an evaluation of slotting measures and storage assignment strategies that generated significant savings in order fulfillment time.

Details

International Journal of Operations & Production Management, vol. 25 no. 10
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 9 May 2016

Chao-Lung Yang and Thi Phuong Quyen Nguyen

Class-based storage has been studied extensively and proved to be an efficient storage policy. However, few literature addressed how to cluster stuck items for class-based…

Abstract

Purpose

Class-based storage has been studied extensively and proved to be an efficient storage policy. However, few literature addressed how to cluster stuck items for class-based storage. The purpose of this paper is to develop a constrained clustering method integrated with principal component analysis (PCA) to meet the need of clustering stored items with the consideration of practical storage constraints.

Design/methodology/approach

In order to consider item characteristic and the associated storage restrictions, the must-link and cannot-link constraints were constructed to meet the storage requirement. The cube-per-order index (COI) which has been used for location assignment in class-based warehouse was analyzed by PCA. The proposed constrained clustering method utilizes the principal component loadings as item sub-group features to identify COI distribution of item sub-groups. The clustering results are then used for allocating storage by using the heuristic assignment model based on COI.

Findings

The clustering result showed that the proposed method was able to provide better compactness among item clusters. The simulated result also shows the new location assignment by the proposed method was able to improve the retrieval efficiency by 33 percent.

Practical implications

While number of items in warehouse is tremendously large, the human intervention on revealing storage constraints is going to be impossible. The developed method can be easily fit in to solve the problem no matter what the size of the data is.

Originality/value

The case study demonstrated an example of practical location assignment problem with constraints. This paper also sheds a light on developing a data clustering method which can be directly applied on solving the practical data analysis issues.

Details

Industrial Management & Data Systems, vol. 116 no. 4
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 14 June 2019

Fabio Sgarbossa, Martina Calzavara and Alessandro Persona

Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A…

Abstract

Purpose

Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A dual-bay VLM order picking (dual-bay VLM-OP) system is a particular solution where the operator works in parallel with the crane, allowing higher throughput performance. The purpose of this paper is to define models for different operating configurations able to improve the total throughput of the dual-bay VLM-OP system.

Design/methodology/approach

Analytical models are developed to estimate the throughput of a dual-bay VLM-OP. A deep evaluation has been carried out, considering different storage assignment policies and the sequencing retrieval of trays.

Findings

A more accurate estimation of the throughput is demonstrated, compared to the application of previous models. Some use guidelines for practitioners and academics are derived from the analysis based on real data.

Originality/value

Differing from previous contributions, these models include the acceleration/deceleration of the crane and the probability of storage and retrieve of each single tray. This permits to apply these models to different storage assignment policies and to suggest when these policies can be profitably applied. They can also model the sequencing retrieval of trays.

Details

Industrial Management & Data Systems, vol. 119 no. 6
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 1 February 2000

Chin Chia Jane

Considering a relay order pick system in a distribution center, proposes a heuristic method based on historical customers’ orders for assigning products into storage

Abstract

Considering a relay order pick system in a distribution center, proposes a heuristic method based on historical customers’ orders for assigning products into storage zones, and constructs a performance index for measuring the continuity of each order handled in the pick system. The objective is to balance workloads among all pickers so each one has almost the same load and the relay pick lane has a continuous flow. The proposed method is illustrated and verified to achieve the objective through empirical data and simulation experiments. Considering the fluctuation in order volume, presents two heuristic methods, also based on historical data, for adjusting the storage location so that the balanced workloads among all pickers and the continuity of the operation lane are not changed. These two methods are illustrated through actual data and verified by simulation experiments.

Details

International Journal of Physical Distribution & Logistics Management, vol. 30 no. 1
Type: Research Article
ISSN: 0960-0035

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Article
Publication date: 9 January 2017

Bhavin Shah and Vivek Khanzode

The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan…

Abstract

Purpose

The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers.

Design/methodology/approach

After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization.

Findings

The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area.

Originality/value

The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations.

Details

International Journal of Retail & Distribution Management, vol. 45 no. 1
Type: Research Article
ISSN: 0959-0552

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Article
Publication date: 1 July 2006

Terry R. Collins, Manuel D. Rossetti, Heather L. Nachtmann and James R. Oldham

To investigate the application of multi‐attribute utility theory (MAUT) to aid in the decision‐making process when performing benchmarking gap analysis.

Abstract

Purpose

To investigate the application of multi‐attribute utility theory (MAUT) to aid in the decision‐making process when performing benchmarking gap analysis.

Design/methodology/approach

MAUT is selected to identify the overall best‐in‐class (BIC) performer for performance metrics involving inventory record accuracy within a public sector warehouse. A traditional benchmarking analysis is conducted on 14 industry warehouse participants to determine industry best practices for the four critical warehouse metrics of picking and inventory accuracy, storage speed, and order cycle time. Inventory and picking tolerances are also investigated in the study. A gap analysis is performed on the critical metrics and the absolute BIC is used to measure performance gaps for each metric. The gap analysis results are then compared to the MAUT utility values, and a sensitivity analysis is performed to compare the two methods.

Findings

The results indicate that an approach based on MAUT is advantageous in its ability to consider all critical metrics in a benchmarking study. The MAUT approach allows the assignment of priorities and analyzes the subjectivity for these decisions, and provides a framework to identify one performer as best across all critical metrics.

Research limitations/implications

This research study uses the additive utility theory (AUT) which is only one of multiple decision theory techniques.

Practical implications

A new approach to determine the best performer in a benchmarking study.

Originality/value

Traditional benchmarking studies use gap analysis to identify a BIC performer over a single critical metric. This research integrates a mathematically driven decision analysis technique to determine the overall best performer over multiple critical metrics.

Details

Benchmarking: An International Journal, vol. 13 no. 4
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 5 May 2015

Venkat R. Kota, Don Taylor and Kevin R. Gue

Puzzle-based storage is a novel approach enabling very dense storage. Previous analytical studies have focussed on retrieval time when one or more usable escort locations…

Abstract

Purpose

Puzzle-based storage is a novel approach enabling very dense storage. Previous analytical studies have focussed on retrieval time when one or more usable escort locations (empty slots) are located near the system input/output location, and on simulation results for more complex situations. The purpose of this paper is to extend analytical results to determine retrieval time performance when multiple escorts are randomly located within the system.

Design/methodology/approach

Closed-form expressions for retrieval time are developed and proven for cases in which the number of free, randomly placed escorts is equal to one or two. Heuristics with associated worst case bounds are proposed for larger numbers of free escorts.

Findings

Puzzle-based storage systems are practical and viable ways to achieve storage density, but retrieval time is heavily dependent upon suitable use of escort locations. Analytical and heuristic methods developed within the paper provide worst-case retrieval time performance in a variety of settings.

Research limitations/implications

As the number of free, randomly located escorts increases, optimal analytical solutions are difficult to obtain. Heuristics provide viable retrieval strategies in these situations, and worst-case bounds are relatively easily developed.

Originality/value

The primarily contribution of this paper is to make theoretical extensions of optimal methods for puzzle-based storage systems. It motivates additional research in multiple-escort systems and provides insights that should prove useful for the development of 3-dimensional puzzle-based systems and for systems in which concurrent item movement is permitted.

Details

Journal of Manufacturing Technology Management, vol. 26 no. 4
Type: Research Article
ISSN: 1741-038X

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Article
Publication date: 16 August 2013

N. Faber, M.B.M. de Koster and A. Smidts

The purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by…

Abstract

Purpose

The purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by task complexity (TC) and market dynamics (MD).

Design/methodology/approach

A multi‐variable conceptual model is developed based on the literature and tested among 215 warehouses using a survey.

Findings

The results suggest that TC and MD are the main drivers of warehouse management, measured by planning extensiveness (PE), decision rules complexity, and control sophistication. Differences between production and distribution warehouses are found with respect to the relationship between assortment changes and PE. Furthermore, TC appears to be a main driver of the specificity of the warehouse management (information) system (WMS).

Research limitations/implications

This paper is based on 215 warehouses in The Netherlands and Flanders (Belgium); future research may test the model on a different sample. More research should be conducted to further validate the measures of the core dimensions of warehouse management.

Practical implications

Different levels of TC and MD characterize warehouses. Such a characterization is a first step in determining generic warehouse functionalities and helping managers to decide on the best software for their warehouse operations.

Originality/value

The paper defines the core dimensions of warehouse management, makes them measurable, tests them and assesses how these drivers impact specificity of WMS. The paper shows that PE in production warehouses is driven by different variables than in distribution centers.

Details

International Journal of Operations & Production Management, vol. 33 no. 9
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 28 September 2018

Şeyma Emeç and Gökay Akkaya

The purpose of this paper is to develop a stochastic multi-criteria decision-making approach to solute the warehouse location problem in the stochastic environment which…

Abstract

Purpose

The purpose of this paper is to develop a stochastic multi-criteria decision-making approach to solute the warehouse location problem in the stochastic environment which contains uncertain condition.

Design/methodology/approach

In developed approach, the weight of criteria was calculated by using the stochastic analytic hierarchy process (SAHP) method. Alternative ranking was made and evaluated by fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje).

Findings

This study dealt with warehouse location selection problem of a supermarket that has sellers in many regions in Turkey and selected proper warehouse.

Originality/value

This study combined SAHP and fuzzy VIKOR methods as a solution approach for warehouse location selection problems.

Details

Journal of Enterprise Information Management, vol. 31 no. 6
Type: Research Article
ISSN: 1741-0398

Keywords

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