Routing policies and COI-based storage policies in picker-to-part systems

Caron, Franco; Marchet, Gino; Perego, Alessandro

doi:10.1080/002075498193651

Cited by 154 publications

(121 citation statements)

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“…However, the depot may also be located at the head of a cross aisle (Caron et al, 1998). This configuration is indicated in Figure 1 by "alternative depot location".…”

Section: Quality Assessment For Another Depot Locationmentioning

confidence: 99%

“…Caron et al (1998) and Le-Duc and De Koster (2005) studied a two-block layout with turnover-based storage policies and with the depot at the head of the middle cross aisle. However, for analytical purposes such a layout is in many aspects similar to an one-block layout with the depot at the head of the left-most aisle.…”

Section: Average Travel Distance Estimationmentioning

confidence: 99%

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Designing the layout structure of manual order picking areas in warehouses

2008

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Order picking is the warehousing process by which products are retrieved from their storage locations in response to customers' orders. Its efficiency can be influenced through the layout of the area and the operating policies. We present a model that minimizes travel distances in the picking area by identifying an appropriate layout structure consisting of one or more blocks of parallel aisles.The model has been developed for one commonly used routing policy, but it is shown to be fairly accurate for some other routing policies as well.

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“…However, the depot may also be located at the head of a cross aisle (Caron et al, 1998). This configuration is indicated in Figure 1 by "alternative depot location".…”

Section: Quality Assessment For Another Depot Locationmentioning

confidence: 99%

Section: Average Travel Distance Estimationmentioning

confidence: 99%

Designing the layout structure of manual order picking areas in warehouses

2008

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“…The place of depot in front of aisles or between the two blocks is planned in Caron et al (1998) study. This is the position where forklift operator takes task and after which returns back for another one [3].…”

Section: Forklift Operationsmentioning

confidence: 99%

Optimising Forklift Activities in Wide-Aisle Reference Warehouse

Burinskienė¹

2015

Int. j. simul. model.

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Nowadays the great attention has to be paid to warehouse. Theoretical analysis shows the need to optimise their activities. This encourages the search of more advanced solutions. Aiming to determine possible improvements, the operations of forklifts are examined in warehouses, and detail solutions are presented.For empirical study author created a simulation model and tested different scenarios. First of all, author examined the new routing method and suggested programming algorithm for forklift route optimization. In the first part of the study possible improvements for put-away activity are analysed, in the second part -improvements for replenishment activity are overviewed. Simulation results showed that the reduction of forklift travel distance is equal from 11.1 % to 35.6 %. Finally, the study ends with detail suggestions: author presented new routing method and forklift routing algorithm. Further, the theoretical results have to be tested in practise.

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“…Using equations (4) and (5), the number of neurons for the ANN1 layers was calculated. Using equation (6), the number of neurons for the remaining ANNs (ANN2 to ANN9) was calculated. …”

Section: Figure 4: Artificial Neural Network Structurementioning

confidence: 99%

“…According to Caron et al [6], adopting allocation methods based on sales volume requires a more 'intensive information' approach that might not be available -for example, when the order frequency is changing in a dynamic environment. In cases like the one analysed here, small businesses usually do not invest enough to improve their processes, and this limits their ability to generate information banks like those that big companies have.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Applied to Assigned Merchandise Location in Retail Sales Systems

Cruz-Domínguez

Santos-Mayorga

2016

SAJIE

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This paper presents an option for improving the process of assigning storage locations for merchandise in a warehouse. A disadvantage of policies in the literature is that the merchandise is assigned allocation only according to the volume of sales and the rotation it presents. However, in some cases it is necessary to deal with other aspects such as family group membership, the physical characteristics of the products, and their sales pattern to design an integral policy. This paper presents an alternative to the aforementioned process using Flexsim ® , artificial neural networks, and genetic algorithms. OPSOMMING'n Metode om die toekenningsproses van stoorplekke vir goedere in 'n pakhuis te verbeter, word voorgehou. 'n Nadeel van die bestaande beleide in die literatuur is dat die goedere slegs toegeken word op grond van die verkoopvolume en die omset wat dit verteenwoordig. In sommige gevalle is dit egter nodig om ander aspekte, soos familie groeplidmaatskap, die fisiese eienskappe van die produkte en hulle verkoopspatroon, te oorweeg om 'n integrale beleid te formuleer. Hierdie artikel beskryf 'n alternatief vir die voorafgenoemde proses deur van Flexsim ® , kunsmatige neurale netwerke en genetiese algoritmes gerbuik te maak.

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Routing policies and COI-based storage policies in picker-to-part systems

Cited by 154 publications

References 0 publications

Designing the layout structure of manual order picking areas in warehouses

Designing the layout structure of manual order picking areas in warehouses

Optimising Forklift Activities in Wide-Aisle Reference Warehouse

Artificial Intelligence Applied to Assigned Merchandise Location in Retail Sales Systems

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