Modeling and evaluating the AVS/RS with tier-to-tier vehicles using a semi-open queueing network

Cai, Xiao; Heragu, Sunderesh S.; Liu, Yang

doi:10.1080/0740817x.2013.849832

Cited by 55 publications

(27 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to Equations (10)- (12) and 14, we can get the waiting time of the lift T l_w k as Equation 15:…”

Section: Timementioning

confidence: 99%

“…But the model was established on the premise of fixed storage structure and equipment parameters. Compared with the open queuing network proposed by predecessors, both Cai [11,12] and Ekren [13] proposed to establish a semi-open queuing network to analyze the shuttle and lift operation system, but this system is only suitable for the serial operation system composed of shuttles and lifts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Task Scheduling Model of Double-Deep Multi-Tier Shuttle System

et al. 2019

View full text Add to dashboard Cite

As a new type of part-to-picker storage system, the double-deep multi-tier shuttle system has been developed rapidly in the e-commerce industry because of its high flexibility, large storage capacity, and robustness. The system consists of a multi-tier shuttle sub-system that controls horizontal movement and a lift sub-system that manages vertical movement. The combination of shuttles and lifts, instead of a stacker crane in conventional automated storage and retrieval system, undertakes inbound/outbound tasks. Because of the complex structure and numerous equipment of the system, task scheduling has become a major difficulty in the outbound operation of the double-deep multi-tier shuttle system. Figuring out methods to improve the overall efficiency of task scheduling operations is the focus of current system application enterprises. This paper introduces the task scheduling problem for the shuttle system. Inspired from workshop production scheduling problems, we minimize the total time of a batch of retrieval tasks as the objective function, applying the modified Simulated Annealing Algorithms (SAAs) to solve the task scheduling problem. In conclusion, we verified the proposed model and the algorithm efficiency, using case studies.

show abstract

“…According to Equations (10)- (12) and 14, we can get the waiting time of the lift T l_w k as Equation 15:…”

Section: Timementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Task Scheduling Model of Double-Deep Multi-Tier Shuttle System

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Autonomous vehicle-based storage and retrieval systems (AVS/RSs) can store and retrieve goods stored on unit loads with high operational efficiency and flexibility. These systems have been adopted by many distribution centers in their high density storage areas, since the introduction by Savoye Logistics at the beginning of the 20th century (Cai et al (2014), Roy et al (2015)).…”

Section: Introductionmentioning

confidence: 99%

“…(7), we need to calculate the state probabilities of the closed queueing network π(s k ). To this end, we first approximate the general distributions of the vehicle service time and the lift service time by Coxian distributions (seeAltiok (1985),Jia & Heragu (2009),Cai et al (2014), andTappia et al (2016)). Then we derive the transition matrix of s k , denoted by Q.…”

mentioning

confidence: 99%

“…Estimation of the performance measures of the fork-join queueing networkTo estimate the performance of the tier-captive AVS/RSs under the parallel processing policy, we have two steps: First, we build an open queueing network by replacing the fork-join node by a flow equivalent server with the service rates obtained in Section 4.1 (seeJia & Heragu (2009),Cai et al (2014),Ekren et al (2014) andTappia et al (2016)). Then, we use the MEMto analyze the open queuing network since it is non-product-form.4.2.1.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems

Zou

Gong

et al. 2016

European Journal of Operational Research

View full text Add to dashboard Cite

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights • We propose a parallel policy for autonomous tier-captive storage/retrieval systems. • A fork-join queueing network is formulated to analyze the system performance. • The parallel policy has advantages in small size systems. • The parallel policy has advantages below a critical transaction arrival rate.

show abstract

Stochastic modeling of multiline orders in integrated storage‐order picking system

Bansal

Roy

2021

Naval Research Logistics

View full text Add to dashboard Cite

Due to demanding service levels in e‐commerce order fulfillment, modeling and analysis of integrated storage and order picking processes in warehouses deserve special attention. The upstream storage system can have a significant impact on the performance of the downstream order picking process. With a particular focus on multiline e‐commerce orders, we develop an analytical modeling framework for integrated analysis of upstream (shuttle‐based storage and retrieval system) and downstream (pick system) networks. To capture the consolidation delays in fulfilling multiline orders, the downstream pick system is modeled with a closed queuing network that includes synchronization nodes. The configuration of the synchronization station is adapted to model the variety of order profiles handled at the pick station. For the downstream closed queuing network, we propose a decomposition‐based solution methodology that results in good solution accuracy. The resulting semi‐open queuing network (SOQN) of the integrated system is analyzed using the matrix‐geometric method (MGM). To improve the accuracy of analytical estimates of the measures, we propose a hybrid simulation/analytical framework, where the performance measures of complex subnetworks are obtained from simulation. We also develop a detailed simulation model of the physical system for validating the analytical and hybrid estimates of the performance measures. The results from experiments indicate that the hybrid simulation/analytical approach reduces the error in the throughput time estimates to 3% from 18% obtained from the analytical model. Then, we investigate the effect of the upstream network configuration (such as the number of storage aisles) and the downstream network configuration (such as the mixed vs. dedicated picking, CONWIP control for orders, order batching) on the order throughput times. Our analysis provides a threshold on the maximum numbers of allowable orders (CONWIP control) and number of aisles beyond which the improvement in average throughput time of the integrated system is marginal. Numerical experiments with high‐order arrivals also highlight that mixed picking in the downstream network can result in significant throughput time reduction in comparison to dedicated picking.

show abstract

Modeling and evaluating the AVS/RS with tier-to-tier vehicles using a semi-open queueing network

Cited by 55 publications

References 20 publications

Task Scheduling Model of Double-Deep Multi-Tier Shuttle System

Task Scheduling Model of Double-Deep Multi-Tier Shuttle System

Modeling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems

Stochastic modeling of multiline orders in integrated storage‐order picking system

Contact Info

Product

Resources

About