An exact optimization method based on dominance properties for the design of AS/RSs

Hamzaoui, Mohammed A.; Arbaoui, Taha; Yalaoui, Farouk; Sari, Zaki

doi:10.1016/j.tre.2020.102204

Cited by 4 publications

(1 citation statement)

References 43 publications

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“…However, some operational characteristics, such as acceleration and deceleration, are not considered by this work and are integrated in subsequent researches (Chang et al , 1995). To this end, the travel time is considered again for both SC and DC cycles but with multi-shuttle and multi-aisle systems as well as different rack configurations (Lerher et al , 2021; Hamzaoui et al , 2021). In particular, Ghomri et al (2009) propose a simulation model based on continuous mathematical functions, which aim to be fairly easy to compute, in order to calculate SC and DC cycle times of a multi-aisle AS/RS.…”

Section: Literature Reviewmentioning

confidence: 99%

AS/R system travel time in class-based storage with different input-output point levels: a proposed formula

Hoshimov

Cagliano

Mangano

et al. 2022

JFM

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Purpose This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels. Design/methodology/approach A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values. Findings The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times. Research limitations/implications The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses. Originality/value This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

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Section: Literature Reviewmentioning

confidence: 99%

AS/R system travel time in class-based storage with different input-output point levels: a proposed formula

Hoshimov

Cagliano

Mangano

et al. 2022

JFM

View full text Add to dashboard Cite

show abstract

Modeling and optimization of expected travel time for multi‐aisle AS/RSs with two‐class‐based storage policy

2024

Naval Research Logistics

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Class‐based storage policy with optimized contour‐shaped class boundary can significantly improve storage system's performance. Surprisingly, this policy has not been explored in widely used multi‐aisle automated storage and retrieval systems (MA‐AS/RSs), which use one storage and retrieval machine to serve multiple aisles with the help of an aisle‐transfer technique. This paper investigates the two‐class‐based storage policy with contour‐shaped class boundary in MA‐AS/RSs that use a transfer car for aisle transfer. The aim is to optimize the system dimensions and class boundary by minimizing system's expected travel time. Based on the approximation of the MA‐AS/RS with a continuous cube and the proposed hierarchical procedure, analytical expected travel time expressions for systems with any dimensions and class boundary are calculated. In addition, based on several proved properties, closed‐form optimal system dimensions and class boundary are derived. Numerical results show the accuracy of our continuous cubic approximation is sufficient. By measuring the performance using the average of expected travel time over all tested systems with various dimensions, we find that (1) class‐based policy with our optimal class boundary can respectively improve the performance by at least 40%, 10%, and 50% compared to three previous policies in the case of 20/80 ABC curve; and (2) system with our optimal dimensions can improve the performance by about 20%–30%. Several managerial insights for warehouse practitioners are presented.

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Automated storage and retrieval system design with variant lane depths

Dong,

Jin

2024

European Journal of Operational Research

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An exact optimization method based on dominance properties for the design of AS/RSs

Cited by 4 publications

References 43 publications

AS/R system travel time in class-based storage with different input-output point levels: a proposed formula

AS/R system travel time in class-based storage with different input-output point levels: a proposed formula

Modeling and optimization of expected travel time for multi‐aisle AS/RSs with two‐class‐based storage policy

Automated storage and retrieval system design with variant lane depths

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