Defining order picking policy: A storage assignment model and a simulated annealing solution in AS/RS systems

Atmaca, Ediz; Ozturk, Ayla

doi:10.1016/j.apm.2012.09.057

Cited by 38 publications

(13 citation statements)

References 21 publications

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“…Class-based storage policy distributes products into classes and for each class it reserves a region within the storage area in which the products are located in any way [12,20,[22][23][24]. A dedicated storage policy reserves each storage location for a specific product and no other products can be stored in that location [6,13,25]. While in randomized storage policy, the product can be allocated in any empty storage location [7].…”

Section: Storage Location Assignment Problem (Slap)mentioning

confidence: 99%

“…These labor force operations cause an increase on warehousing costs. Thus, improving the efficiency of the OP process plays an important part in reducing warehousing costs and, consequently, supply chain costs [6,7]. For this, OPS usually use four methods, which are (1) zoning policies, (2) routing policies, (3) order batching, and (4) storage location assignment.…”

Section: Introductionmentioning

confidence: 99%

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Multi-criteria approach for products classification and their storage location assignment

Fontana

Nepomuceno

2016

Int J Adv Manuf Technol

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Even small improvements in storage operations can bring significant benefits in customer response time, increasing the level of service offered. However, a company cannot offer high level of service for all products. In this sense, one of the ways used to optimize the activities for order picking is the study of storage location assignment problem (SLAP). Thus, this paper proposed a multi-criteria decision model to perform the products classification and to solve the SLAP in a multi-layer warehouse. The ELECTRE TRI method is used to define the shelf level for each product, and the ELECTRE III method is used to establish a fixed location for each product on the shelf it belongs to. The great advantage of this model is that there is not trade-off among the criteria, and it is able to consider several criteria simultaneously. However, the main goal is not optimization, but the search for a storage operations performance balance, considering multiple criteria, allowing for a better inventory management when consideringprofitabilitycriteria,for example,andimprovement inthe order picking operations, through the demand and space required criteria. In addition, it considers the preferences of the decision maker.

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Section: Storage Location Assignment Problem (Slap)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-criteria approach for products classification and their storage location assignment

Fontana

Nepomuceno

2016

Int J Adv Manuf Technol

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“…On implementing simulated annealing, the temperature is reduced gradually and this is called temperature schedule until it is frozen when the temperature is equal to 1. Simulated annealing has found many successful applications such as identification of order picking policy (Atmaca and Ozturk, 2013), vehicle routing (Baños et al, 2013), design of pre-stressed concrete precast road bridges (Martí et al, 2013), inferring maximum parsimony phylogenetic (Richer et al, 2013) and mixed model assembly (Manavizadeh et al, 2013). Simulated annealing is used to model a correlation model.…”

Section: Simulated Annealingmentioning

confidence: 99%

Introduction to Artificial Intelligence based Decision Making

Marwala¹

2015

Causality, Correlation and Artificial Intelligence for Rational Decision Making

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In this chapter, decision making which is based on causality, correlation and artificial intelligence is introduced. The concept of correlation is introduced and is applied to build a correlation function. Furthermore, it relates causality to correlation and uses it to build a causal function. Artificial intelligence methods are introduced and these include neural networks, particle swarm optimization, genetic algorithm and simulated annealing. It describes decision making and outlines the rest of the book. 1 Causality, Correlation and Artificial Intelligence for Rational Decision Making Downloaded from www.worldscientific.com by KAINAN UNIVERSITY on 02/04/15. For personal use only.

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“…Facing such an NP-hard problem, intelligent algorithms have obvious advantages over other methods. Some scholars [15][16] have adopted the simulated annealing (SA) algorithm to build an allocation model for goods locations using a dedicated storage strategy. Some scholars [17] have employed the genetic algorithm (GA) in computer simulation of the online scheduling system.…”

Section: Introductionmentioning

confidence: 99%

Development of Optimization Model and Algorithm for Storage and Retrieval in Automated Stereo Warehouses

Bingkun¹,

Zhu²,

Yan³

et al. 2019

JESA

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With the continuous development of the market economy, the tobacco industry is rapidly expanding in China. There are now numerous cigarette retailers across the country, which distribute multiple types of cigarettes to consumers in small batches and multiple times. Against this backdrop, the traditional warehouse storage and retrieval (S/R) approach, an integration of the radiofrequency identification (RFID) and manual sorting, no longer satisfies the market demand. Most cigarette distribution centres now use automated stereo warehouses, which face the com-plex and realistic problem of goods S/R with multiple stackers, multiple carriers and irregular goods locations. After analysing the features of the automated storage and retrieval system (AS/RS), this paper introduces the bacterial foraging optimization (BFO) algorithm to optimize the AS/RS in light of the actual work conditions. Firstly, a model framework was set up based on the production reality and algorithm constraints. Next, the model was solved by the bionic algorithm BFO. Finally, a numerical example was selected to verify the effectiveness of the algorithm. The results show that the BFO can effectively shorten the operation time and improve the S/R efficiency. The research findings provide a scientific and rational plan for automated ware-housing in complex environments.

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Defining order picking policy: A storage assignment model and a simulated annealing solution in AS/RS systems

Cited by 38 publications

References 21 publications

Multi-criteria approach for products classification and their storage location assignment

Multi-criteria approach for products classification and their storage location assignment

Introduction to Artificial Intelligence based Decision Making

Development of Optimization Model and Algorithm for Storage and Retrieval in Automated Stereo Warehouses

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