A bi-directional flow-rack automated storage and retrieval system for unit-load warehouses

Flow-rack is a multi-deep rack containing multi-row and multi-column slope bins. Traditionally, bins slope in the same direction in a flow-rack to make unit-loads slide from the storage face to the retrieval face driven by gravity, which cause unit-loads are stored to the storage face and retrieved from the retrieval face. In this paper, a bi-directional flow-rack (BFR) is designed, in which bins in adjacent columns slope to opposite directions. In each side of a BFR, unit-loads are stored in half of the bins and retrieved from the other half. Therefore, dual-command (DC) operations could be simultaneously performed on both faces and blocking unit-loads are re-stored to available bins on the same face directly. We develop a travel time model for BFR systems, which provides the throughput baseline for different configurations of BFR. A DC operation generation method is introduced for BFR systems. Simulation experiments are conducted to evaluate the effectiveness of the BFR travel time model, to compare the throughput performance between BFR and SFR systems and to evaluate the performance of the proposed DC operation generation method.     

Sequencing the storages and retrievals for flow-rack automated storage and retrieval systems with duration-of-stay storage policy

Sequencing of storages and retrievals is an important topic in the automated storage and retrieval system (AS/RS), which largely influences the throughput performance and the operational cost of an AS/RS. In this paper, the problem of sequencing the storages and retrievals in a flow-rack AS/RS with duration-of-stay storage policy is analysed and a two-step heuristic called the grouping-matching method is proposed for minimising the total travel time of operations. The proposed grouping-matching method assigns unit-loads into groups in the grouping step and matches groups and bins of flow rack in the matching step. Two grouping heuristics are designed for the grouping step. The matching subproblem is formulated as an assignment to be solved. Simulation experiments are conducted to evaluate the effectiveness and efficiency of the grouping-matching method and the two grouping heuristics used for the grouping subproblem.     

On sequencing policies for unit-load automated storage and retrieval systems

Automated Storage and Retrieval System (AS/RS) performance highly depends on the characteristics of the mechanical equipment. However, once the system has been physically implemented, achieving its maximum efficiency depends on the way the system is operated. This paper shows that request sequencing (i.e. planning the order in which storage and retrieval requests are performed) is of paramount importance in AS/RS performance. This paper reviews and adapts the most popular storage and sequencing policies to dynamic contexts, and then it proposes a ‘sequencing mathematical model’ (SMM) to simultaneously solve the sequencing and storage location problems. Extensive computational results based on a thorough simulation experiment plan confirm that performing the requests in the right sequence can have a positive impact on AS/RS performance. Our results show that the proposed SMM regularly outperforms other methods. When used in a dynamic context, the proposed SMM may yield up to a 25% reduction in average travel-time compared to the situation where a no-sequencing method is applied.     

An efficient cycle time model for autonomous vehicle storage and retrieval systems

A computationally efficient cycle time model for conceptualizing autonomous vehicle storage and retrieval systems and comparing their performance with crane-based automated storage and retrieval systems is presented. The model is based on an iterative computational scheme exploiting random storage assumptions and queuing model approximations. Relative to earlier models, the procedure scales up efficiently for large problems thereby enabling more extensive search of a design solution space. Simulation based validation studies suggest that model accuracy is adequate for system conceptualization. The procedure is demonstrated using realistically sized sample problems.     

Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.     

Modelling load retrievals in puzzle-based storage systems

Puzzle-based storage systems are a new type of automated storage systems that allow storage of unit loads (e.g. cars, pallets, boxes) in a rack on a very small footprint with individual accessibility of all loads. They resemble the famous 15-sliding tile puzzle. Current models for such systems study retrieving loads one at a time. However, much time can be saved by considering multiple retrieval loads simultaneously. We develop an optimal method to do this for two loads and heuristics for three or more loads. Optimal retrieval paths are constructed for multiple load retrieval, which consists of moving multiple loads first to an intermediary ‘joining location’. We find that, compared to individual retrieval, optimal dual load retrieval saves on average 17% move time, and savings from the heuristic is almost the same. For three loads, savings are 23% on average. A limitation of our method is that it is valid only for systems with a very high space utilisation, i.e. only one empty location is available. Future research should investigate retrieving multiple loads for systems with multiple empty slots.     

A shift-based sequencing method for twin-shuttle automated storage and retrieval systems

The continuing need for high-throughput Automated Storage and Retrieval Systems (AS/RS) has lead to the introduction of storage/retrieval machines that can carry more than one unit-load. However, this technology involves a large capital investment so careful operating methods are desired to make the most of its capabilities. In this paper, we study a shift-based sequencing problem for twin-shuttle AS/RS, where depletion (retrieval operations) and replenishment (storage operations) of items occur over different shifts. For example, certain warehouses or distribution depots deplete their items in stock during morning shifts and replenish during later shifts. We show that this problem can be transformed into the minimum-cost perfect matching problem and present an efficient polynomial-time optimum method that can achieve a large throughput gain over other methods. We also provide average-case and lower bound analyses for this problem.     

Application of storage consolidation intervals to approximate random storage transaction times with closest open location load dispatching

A new modelling approach is proposed for estimating storage/retrieval transaction times in warehouse systems using random storage and closest open location load dispatching. The method is based on estimating intervals between consolidations of the active storage envelope defined by the most remote occupied storage position in a warehouse. This enables the calculation of the expected number of interspersed storage vacancies within the storage envelope which can then be applied in transaction time calculations. Computational results for test problems suggest that the method performs well relative to alternative procedures reported in the literature.     

Analytical model to estimate performances of autonomous vehicle storage and retrieval systems for product totes

In today's competitive scenario of increasingly faster deliveries and smaller order sizes, material-handling providers are progressively developing new solutions. A recent, automated material-handling technology for unit load storage and retrieval consists of an autonomous vehicle storage and retrieval system (AVS/RS). The present paper presents an analytical model to estimate the performances (the transaction cycle time and waiting times) of AVS/RS for product tote movement. The model is based on an open queuing network approach. The model effectiveness in performance estimation is validated through simulation.     

Heavy traffic analysis of a single vehicle loop in an automated storage and retrieval system

We consider an automated storage/retrieval system in which cargo moves between the storage/retrieval machines and the system entrance/exit stations through a single automated vehicle loop. Past studies indicated that the cargo waiting time in the loop is affected by the dispatching rules, which govern the sequence of the cargo to be handled. In this paper, we show that the loop configuration, which has received little research attention, also has a big impact on the cargo waiting time. When the first-come-first-served dispatching rule is used, we derive the relationship between the number of stations and the ratio of the average cargo retrieval time to the average cargo storage time. When the first-encountered-first-served dispatching rule is used, we show that even the arrangement of the input channel and the output channel of a station can have significant impact on the cargo waiting time. Furthermore, we derive a formula for the vehicle visit rate for each station under heavy traffic conditions. This formula helps to explain the phenomenon that the waiting times at different stations can be very different even when the loop is symmetrically designed and the cargo arrival rates to the stations are similar. In addition to analytical models, we use simulations to evaluate the performance of different loop configurations. Our research suggests that a substantial improvement can be achieved by making proper adjustments to the loop configuration.     

自动化存取系统控制优化研究综述

控制优化是提高自动化存取系统效率的有效途径。对比分析了自动化存取系统控制优化策略在生产和配送领域的应用特点,指出生产领域自动化存取系统控制优化主要关注货物出库的实时性,而配送领域则更关注货物出入库的总体平衡。调研了货位分配、停靠点策略、存取指令排序、订单批次化等主要控制优化问题的国内外研究成果,分析了自动化存取系统控制优化未来的研究方向。     

Sequencing approaches for multiple-aisle automated storage and retrieval systems

Automated storage and retrieval systems (AS/RS) are used in high velocity distribution centres to provide accurate and fast order processing. While almost every industrial system is comprised of many aisles, most of the academic research on the operational aspects of AS/RS is devoted to single-aisle systems, probably due to the broadly accepted hypothesis proposing that an m aisles system can be modelled as m 1-aisle independent systems. In this article, we present two multi-aisles sequencing approaches and evaluate their performance when all the aisles are managed independently first, and then in a global manner. Computational experiments conducted on a multi-aisle AS/RS simulation model clearly demonstrate that a multi-aisle system cannot be accurately represented by multiple single-aisle systems. The numerical results demonstrate that, when dealing with random storage, globally sequencing multi-aisle AS/RS leads to makespan reductions ranging from 14 to 29% for 2- and 3-aisle systems, respectively.     

A heuristic travel time model for random storage systems using closest open location load dispatching

A heuristic method is proposed for estimating travel times in unit load random storage systems where incoming loads are dispatched to the closest available storage positions. A queuing model representation is used where servers correspond to storage positions and the service rate is based on the turnover distribution of stored loads. The resultant state distribution is applied to approximate storage position occupancy probabilities useful for generating storage and retrieval travel time estimates. Computational results suggest that the heuristic procedure yields smaller errors in random storage travel time estimates than alternative models.     

Travel time model for double-deep shuttle-based storage and retrieval systems

Technological developments in the global supply chain have changed processes in warehousing. This reflects in short response time in handling the orders, which has a consequence on high automation degree in warehousing. An important part of automated warehouses is presented by shuttle-based storage and retrieval systems (SBS/RS), which are used in practice when demand for the throughput capacity is high. In this paper, analytical travel time model for the computation of cycle times for double-deep SBS/RS is presented. The advantage of the double-deep SBS/RS is that fewer aisles are needed, which results in a more efficient use of floor space. The proposed model considers the real operating characteristics of the elevators lifting table and the shuttle carrier with the condition of rearranging blocking totes to the nearest free storage location during the retrieval process of the shuttle carrier. Assuming uniform distributed storage locations and the probability theory, the expressions for the single and dual-command cycle of the elevators lifting table and the shuttle carrier have been determined. The proposed model enables the calculation of the expected cycle time for single- and dual-command cycles, from which the performance of the double-deep SBS/RS can be evaluated. The analysis show that regarding examined type of the double-deep SBS/RS, the results of the proposed analytical travel time model demonstrate good performances for evaluating double-deep SBS/RS.     

Deadlock control of autonomous vehicle storage and retrieval systems via coloured timed Petri nets and digraph tools

This paper addresses the deadlock control problem for the autonomous vehicle storage and retrieval system (AVS/RS). For an AVS/RS with several autonomous vehicles running in bi-direction, deadlock control is one of the key issues in the implementation of AVS/RS. The cycle-deadlock is the main type of deadlock in AVS/RS. In the paper, the dynamic model of AVS/RS is investigated by using coloured timed Petri nets (CTPN). Based on the CTPN model, a route digraph is built to detect cycle-deadlock in AVS/RS with digraph tools; the necessary and sufficient conditions of deadlock-free are established. Moreover deadlock-free control policies are proposed, the critical state in deadlock free is also identified and FCFS policy is applied to solve it. Finally, a case study is given to validate the policies.     

The impact of dwell point policy in an Automated Storage/Retrieval System

Automated storage and retrieval systems (AS/RS) are devices that allow intensive storage of materials. They can improve the supply chain performance, assuring more available volume for storage, lower labour costs and higher handling throughput of warehousing. Furthermore, the automated control allows the probability of errors in storage and retrieval to be minimised, along with the probability of product damage during movements. The purpose of the paper is to find the best solution in order to find the optimal dwell point policy, among different rules, able to minimise the travel time and distance travelled by stacker cranes, and consequently warehousing costs. An original and innovative model was developed in order to investigate the dwell point position for random allocation of unit loads. A software platform was developed to validate the proposed model by computer simulations. The performance of the system was analysed in a parametric/continuous way, varying at the same time the number of spans and levels, the height of the input/output point and the interval between requested missions. The results show that the developed model allowed convenience areas to be identified among the policies in which the travel time, distance travelled, and consequently warehousing costs are minimised, by varying different parameters.     

Picking strategies to the two‐carousel‐single‐server system in an automated warehouse

Abstract

An automatic storage system comprised of two storage carousel conveyors and a retrieval apparatus integrated by computers has been considered in this paper. The order picking problem for such a two‐carousel‐single‐server system is presented here. The retrieval time is analyzed by a two‐stage solution procedure for the scheduling sequence of retrieving items from the system in order to satisfy an order requirement. The analytical results can be directly applied for the scheduling of the carousel storage system.     

An Efficient Encrypted Speech Retrieval Based on Unsupervised Hashing and B+ Tree Dynamic Index

Existing speech retrieval systems are frequently confronted with expanding volumes of speech data. The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’ real-time retrieval requirements. This study proposes an efficient method for retrieving encryption speech, using unsupervised deep hashing and B+ tree dynamic index, which avoid privacy leakage of speech data and enhance the accuracy and efficiency of retrieval. The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan (DGHV) Fully Homomorphic Encryption (FHE) technique, which encrypts the original speech. In addition, this research employs Residual Neural Network18-Gated Recurrent Unit (ResNet18-GRU), which is used to learn the compact binary hash codes, store binary hash codes in the designed B+ tree index table, and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech. External B+ tree index technology is applied to achieve dynamic index updating of the B+ tree index table, thereby satisfying users’ needs for real-time retrieval. The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84% compared to the existing unsupervised hashing methods. The retrieval efficiency is greatly improved. Compared to the method of using hash index tables, and the speech data’s security is effectively guaranteed.     

A dynamic threshold-based local mesh ternary pattern technique for biomedical image retrieval

Many content-based image retrieval techniques like local binary pattern (LBP), local ternary pattern (LTP), local mesh peak valley edge pattern (LMePVEP), local mesh ternary pattern (LMeTerP), etc. extract texture features of an image for retrieval purposes. These techniques use fixed threshold to encode the input image and selection of such threshold value is not guided, that is, a chosen threshold may not be optimal for all images in the database. Moreover the performance of these texture-based static threshold algorithms also decreases if the input images are noisy. In this paper, a dynamic threshold value-based local mesh ternary pattern method is proposed in which the threshold value is chosen from the neighborhood of a central pixel using median of all pixels. The proposed modification reduces the overall effect of noise component and thereby improves the average retrieval rate (ARR) and average retrieval precision (ARP) of the original technique. The proposed modified technique has been compared with five other image retrieval approaches to prove its worthiness - the original local mesh ternary pattern technique (LMeTerP), a local ternary pattern technique (LTP), a Best ensemble technique, a multi-label classification CNN model and a CNN-based model of the proposed approach using a VIA ELCAP lung database and an Emphysema database. An improvement of 3.92% in ARR and 2.53% in ARP is observed over the basic local mesh ternary pattern method. Further the proposed modification has been combined with CNN concept and its results have also been analyzed.     

一种提高TRMM测雨雷达反演准确性的方法(英文)

热带降雨测量卫星所携带的测雨雷达是世界上第一颗星载测雨雷达,对其反演算法展开研究在算法开发及数据应用等方面具有重要意义.本文在介绍NASA与JAXA反演雷达反.射率因子的标准算法的基础上,对反射率因子反演算法进行了改进.改进算法根据星载测雨雷速每个观测单元上的降雨率计算出等效雨滴直径,对不服从瑞利散射的观测单元的反射率因子值进行修订,然后再执行衰减订正.本文采用了更合理的5 km×5 km× 1.5 km三维网格,将处理结果与地基雷达数据进行了点对点的定性与定量比较.结果表明,改进算法以较小的计算量增加为代价,获得了反演精度的提高.