Shuttle-based Storage Research Articles

Analytical examination of shuttle-based storage and retrieval systems with multiple-capacity lifts

The unbroken trend towards e-commerce and the ever-increasing demands on storage technology present the providers of storage systems with ever greater challenges. One way to meet these requirements is to significantly enhance warehouses’ handling systems. Multiple capacity lifts in tier-captive single-aisle shuttle-based storage and retrieval systems (SBS/RS) are a method to raise the throughput performance of such systems. Therefore, a straightforward calculation approach is presented based on a cycle time model combined with a time-continuous single open Markovian queue with limited capacity. A comparison of the invented approach to a discrete-event simulation (DES) is made to validate it. Finally, a numerical example of the influences of the different handling capacities and their usage in the design process of SBS/RS is depicted. The result is that with double the handling capacity, the throughput increases by about 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$50\\%$$\\end{document}. Another result is sorting the stops within one handling cycle, which leads to a significantly higher throughput.

Scheduling optimization of tier-captive four-way shuttle-based storage and retrieval systems with multiple lifts

The four-way shuttle-based storage and retrieval system (FSS/RS) handles retrieval transactions through shuttles moving horizontally in four directions and lifts moving vertically. The scheduling process and working route of both are important problems for daily operations. This article constructs a scheduling model for the tier-captive FSS/RS with multiple lifts and designs a two-stage optimization heuristic algorithm (OHA). A heuristic assignment algorithm is proposed to determine the retrieval request sequence, and the route-generation stage adopts an improved A-star algorithm with a multi-phase conflict avoidance method to generate shuttle conflict-free routes. Simulation results demonstrate that OHA can reliably generate high-quality solutions, with a low degree of fluctuation in the results, not exceeding 0.5%. The proposed scheduling method outperforms its competitors in all instances, reducing the makespan by 8%. Moreover, the evidence shows that the proposed method can obtain the most competitive scheduling scheme in FSS/RS with more shuttles and lifts.

A Novel Parts-to-Picker System with Buffer Racks and Access Racks in Flexible Warehousing Systems

With the tremendous development of the logistics industry, the global market of automated warehousing has been growing rapidly. Meanwhile, the warehousing industry shows drawbacks, such as low storage capacity and poor efficiency. By comparing and analyzing the shuttle-based storage and retrieval system (SBS/RS), miniload automated storage and retrieval system (AS/RS), and KIVA system, a novel efficient parts-to-picker approach in flexible warehousing systems is proposed. Among them, buffer racks and access racks, associated with the access of automated mobile robots (AMRs) and stackers are used. The results show that compared with other parts-to-picker systems (such as the KIVA system), this system provides a significant increase in storage capacity (more than three times), and the picking efficiency is also very high at various layout scales, where the picking efficiency is no less than the KIVA system when the number of AMRs reaches the max. The novel system is suitable for small-, medium-, and large-scale warehouses in terms of showing high capacity and producing excellent space utilization. More importantly, this system can easily compete with its traditional counterparts by using a layout of high density without much increase in cost. This sustainable improvement realizes the efficient utilization of spatial resources and provides important support for the construction of green supply chains.

Transaction Processing Policies in a Flexible Shuttle-based Storage and Re-trieval System by Real-time Data Tracking under Agent-based Modelling

This study investigates priority assignment rules (PARs) for transaction processing in automated warehouses featuring a shuttle-based storage and retrieval system (SBSRS). By incorporating real-time data tracking through agent-based modeling, the research explores the unique aspect of the SBSRS design, which involves flexible travel of robotic order picker shuttles be-tween tiers. The paper proposes PARs under agent-based modeling to enhance multi-objective performance metrics, including average flow time (AFT), maximum flow time (MFT), outlier transaction AFT, and standard deviations of flow times (SD) within the system. Experimental evaluations are conducted with various warehouse designs, comparing the results against commonly used static scheduling rules. The findings demonstrate that real-time tracking policies significantly improve system performance. Specifically, prioritizing the processing of outliers based on transaction waiting time enhances MFT, SD, and other performance metrics, while minimizing adverse effects on AFT. Certain rules exhibit notable improvements in MFT and SD, while others achieve the lowest AFT values among all experiments. This paper contributes to the existing literature by presenting a multi-objective performance improvement procedure and highlighting the advantages of real-time data track-ing-based scheduling policies in automated warehousing systems.

A method of system selection for shuttle-based storage and retrieval system considering cost and performance

A method of system selection for shuttle-based storage and retrieval system considering cost and performance

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

ABSTRACT The paper presents an analytical model for travel time evaluation in double-deep, triple-deep, quadruple-deep and fivefold-deep tier-captive shuttle-based storage and retrieval system (SBS/RS). Under the assumption of the deepest location rule for the storage process and the nearest neighbour rule for the retrieval process, the expressions for single-command and dual-command cycle times of the shuttle vehicle and elevator are developed, from which the SBS/RS performance can be estimated. The model based on the probability theory enables the evaluation of all individual times that make up the cycle times and assessment of the average number of totes relocated during a retrieval process. Special attention is devoted to the modelling of the relocation of totes which block access to the requested tote during the retrieval process. The validity of the analytical model is examined via the developed simulation model. The given case study shows that the proposed analytical travel time model results match the results of the simulation model. The presented modelling strategy could be applied to bigger system racking depths following the same modelling logic.

An analytical approach of multiple-aisle shuttle-based storage and retrieval systems

This paper deals with a method for performance calculation of shuttle-based storage and retrieval system (SBS/RS) with tier-captive aisle-changing shuttles and different storage strategies. The shuttles are assigned to a certain number of aisles in this system. The invented approach takes place in the design process of SBS/RS. A continuous time open-queueing system with a limited capacity approach is applied. A discrete spatial value approach determines the inter-arrival times and service times. A probability-based model mentions the aisle changing. This approach is validated by comparison to a Monte-Carlo simulation. A European material handling provider gave the data used in this comparison to validate this approach. Finally, an example of the usage in the design process of SBS/RS of the invented analytical approach is depicted. The result is an increase in throughput with an increasing number of aisles per shuttle. Likewise, the storage strategy greatly influences the throughput between random storage and retrieval and same aisle storage and retrieval.

Retrieval request scheduling in a shuttle-based storage and retrieval system with two lifts

We study a shuttle-based storage and retrieval system with two independent lifts shared in a single mast. In such a system, two lifts move simultaneously but cannot pass each other, and each retrieval request is finished with the cooperation of a lift and a shuttle. Therefore, given a set of retrieval requests, the retrieval request scheduling problem consists of determining the sequence in which the requests are retrieved and assigning each request to a lift with the objective of minimizing the makespan, considering both the lift-lift interaction and lift-shuttle interaction. The problem is formulated as a mixed-integer programming model and proved to be NP-hard. We propose a decomposition-based adaptive large neighborhood search heuristic to quickly compute near-optimal solutions, using the property that the assignment of requests to lifts for a given retrieval sequence can be exactly solved in polynomial time by a dynamic programming approach. Numerical results indicate that our algorithm achieves a lower makespan than the methods proposed in the literature and used in practice. We also apply the proposed algorithm using real data to a realistic setting that considers multiple planning horizons, showing that it significantly outperforms the policy the company currently uses.

Cost and performance comparison of tier-captive SBS/RS with a novel AVS/RS/ML

This paper introduces a novel autonomous vehicle-based storage and retrieval system that utilizes movable lifts (AVS/RS/ML), proposed as an alternative to the tier-captive shuttle-based storage and retrieval system (SBS/RS). The newly proposed system aims to provide an affordable solution with highly utilised AGVs, that can also perform operations out of warehouse. The performance of this novel system is compared with the equivalent tier-captive SBS/RS warehouse design, where each shuttle is dedicated in a specific tier in that design. The comparison is based on the initial system investments costs, throughput rates, and average utilisation of lifts/MLs in the system. Collision prevention rules are also applied to AVS/RS/ML, and its performance is tested through simulation. The results show that the tier-captive SBS/SR system becomes cost-efficient under high throughput rate requirements, while the AVS/RS/ML technology is preferred for relatively moderate and low process rate requirements. The unit-cost per month performance metric of AVS/RS/ML is less sensitive to an increase in number of tiers in the system, compared to the tier-captive SBS/RS case, indicating that AVS/RS/ML may be promising for high-tier warehouse system designs.

Research on schedling optimization of four-way shuttle-based storage and retrieval systems

In this paper, we take the four-way shuttle system as the research object and establish the mathematical model of scheduling optimization based on the minimum time for the in/out operation optimization and path optimization scheduling problems of the four-way shuttle system. An improved genetic algorithm is used to solve the task planning, and an improved A* algorithm is used to solve the path optimization within the shelf level. The conflicts generated by the parallel operation of the four-way shuttle system are classified, and the improved A* algorithm based on the time window method is constructed for path optimization through the dynamic graph theory method to seek safe conflict-free paths. Through simulation example analysis, it is verified that the improved A* algorithm proposed in this paper has obvious optimization effect on the model of this paper.

Modelling Analysis of a Four-Way Shuttle-Based Storage and Retrieval System on the Basis of Operation Strategy

In the context of sustainable development, this paper rationalises the outbound process of a four-way shuttle system with a focus on their modelling, performance evaluation and configuration using a parallel operation strategy to reduce resource waste, thus achieving sustainable development. The parallelism of the hoist and shuttle is innovatively incorporated into the four-way shuttle system, so the modelling content is divided into parallel and serial types. In the parallel operation strategy model, a separation–aggregation queueing network model is constructed, and the open-loop queueing network is innovatively solved using the maximum entropy method. In the serial operation strategy model, a semi-open-loop queuing network is constructed and solved using the geometric matrix method. By varying different parameters, the accuracy of the model is verified by Arena simulation with an error range of 10% or less, and the error of the system performance index calculation is reduced by 20% compared with the existing methods. Setting up 18 different sizes of shuttle systems provided a better performance than a single serial-operation strategy through the addition of parallel strategies, with an average reduction of 12.6% in the system response time and a minimum reduction of 1.8%. The conclusions of this paper were verified on the basis of an arithmetic case analysis.

Shuttle-Based Storage and Retrieval Systems Designs from Multi-Objective Perspectives: Total Investment Cost, Throughput Rate and Sustainability

This paper studies performance comparison of two shuttle-based storage and retrieval system (SBS/RS) configurations developed on flexible or non-flexible travel policies of shuttles in the system. In the non-flexible SBS/RS, a shuttle is dedicated to a tier so that it cannot travel out of its dedicated aisle and tier. A lifting mechanism is installed in each aisle to provide vertical travel for loads. In flexible SBS/RS, shuttles can travel between tiers by a separate lifting mechanism installed on the other edge point of each aisle. The advantage of that flexible design is that there might be decreased number of shuttles settling in the system compared to the non-flexible design. We simulate the two system configurations and conduct an experimental design for the comparison purpose. Based on the three-performance metrics: total investment cost, throughput rate and energy consumption per transaction, the results show that mainly the flexible system provides better results which might be considered as future system investment for SBS/RS.

Transaction selection policy in tier-to-tier SBSRS by using Deep Q-Learning

ABSTRACT This paper studies a Deep Q-Learning (DQL) method for transaction sequencing problems in an automated warehousing system, Shuttle-based Storage and Retrieval System (SBSRS), in which shuttles can move between tiers flexibly. Here, the system is referred to as tier-to-tier SBSRS (t-SBSRS), developed as an alternative design to tier-captive SBSRS (c-SBSRS). By the flexible travel of shuttles between tiers in t-SBSRS, the number of shuttles in the system may be reduced compared to its simulant c-SBSRS design. The flexible travel of shuttles makes the operation decisions more complex in that system, motivating us to explore whether integration of a machine learning approach would help to improve the system performance. We apply the DQL method for the transaction selection of shuttles in the system to attain process time advantage. The outcomes of the DQN are confronted with the well-applied heuristic approaches: first-come-first-serve (FIFO) and shortest process time (SPT) rules under different racking and numbers of shuttles scenarios. The results show that DQL outperforms the FIFO and SPT rules promising for the future of smart industry applications. Especially, compared to the well-applied SPT rule in industries, DQL improves the average cycle time per transaction by roughly 43% on average.

Scheduling shuttles in deep-lane shuttle-based storage systems

Deep-lane shuttle-based storage systems with forklifts are widely used in bulk storage and finished-goods warehouses that require dense storage paired with high operational efficiency. In such a system, automated shuttles take care of the movements of loads within the storage lanes, and forklifts take care of the horizontal and vertical movements of loads. Since shuttles are expensive, the number of shuttles in the system is typically smaller than the number of storage lanes, so shuttle transfers are required with the help of the forklift. This paper focuses on optimizing the schedule: Given a set of retrieval requests and shuttles, how can the shuttle transfer sequence and the retrieval request sequence be arranged to minimize the makespan? A mathematical model is formulated. Since the problem is NP-hard, an efficient two-stage heuristic is proposed to compute near-optimal solutions. This study’s numerical results show that the two-stage heuristic can provide high-quality solutions in reasonable time. Compared to straightforward heuristics used in practice and in the literature, the makespan can be reduced considerably. The proposed two-stage heuristic can also be used to decide the optimal shuttle fleet size.

Shuttle-Based Storage and Retrieval System: A Literature Review

While the e-commerce logistics industry is developing rapidly, its sustainable development has received certain attention. The ultimate goal of sustainable development is to achieve common, coordinated, fair, efficient, and multi-dimensional development. To promote the sustainable development of logistics, the automation technology of warehousing is undoubtedly an excellent breakthrough, since the automation technology can not only make the warehousing system efficient and with a low-error rate, but also affect the energy consumption of the warehousing system. This paper studies the Shuttle-Based Storage and Retrieval System (SBS/RS) in automated warehousing. Moreover, the paper classifies the existing literature into three categories: Physical design (including depth, configuration, and number of tiers); control strategy (including scheduling rules, storage strategies, scheduling command, and interference); and performance evaluation (including throughput, time, and energy). These categories are all factors that warehouse designers must consider when designing a system. Finally, this paper proposes future research directions for SBS/RS: Adding speed metrics, limiting buffer size, targeting space constraints, applying four-way shuttles, and increasing the carrying capacity of a single machine.

Quantum behaved particle swarm optimization of inbound process in an automated warehouse

The inbound process is of great importance in enhancing the efficiency of automated warehouse operations. This study investigates an optimization problem on the inbound warehouse process by coordinating multiple resources in a type of automated warehouse system, i.e., Shuttle-Based Storage and Retrieval System (SBS/RS). A mixed-integer programming model is formulated to determine the assignment decisions of the pallets towards three types of the resources in the SBS/RS (i.e., forklifts, lifts and shuttles), the sequencing & timing decisions of these three types of resources for transporting the pallets. Then, a novel solution method, called Adaptive Quantum behaved Particle Swarm Optimization (AQPSO) algorithm, is designed to solve the proposed model. The introduction of the quantum mechanism prevents the algorithm from falling into a local minimum. The integration of the adaptive adjustment strategy improves the efficiency of the algorithm by dynamically adjusting the search scale. The efficiency of the proposed algorithm is verified by comparative experiments that use the CPLEX solver and the basic particle swarm optimization algorithm as rivals. The experimental results indicate that the proposed algorithm have an advantage in the solution quality and the computing time. A series of sensitivity analyses are also conducted to bring out some managerial insights. For example, it is beneficial to reduce energy consumption by adjusting the relative velocity and power of the three types of equipment, and setting the best ratios of shuttles to forklifts.

An analytical approach for a performance calculation of shuttle-based storage and retrieval systems with multiple-deep and class-based storage

ABSTRACT This paper presents a method for determining the performance of shuttle-based storage and retrieval systems (SBS/RS) with tier-captive, single-aisle shuttles serving tiers of multiple-deep storage and using a class-based storage policy. This approach is used in the design process of SBS/RS and in the upgrading process of existing SBS/RS. With this approach, it is possible to evaluate the improvement in the performance of multiple-deep storage system by applying a class-based storage policy. The basis of this calculation method is a continuous-time, open-queueing system with limited capacity. The cycle times of lifts and shuttles, as determined by a spatial value approach, combined with a probability-based approach to mention the storage policy. To take the multiple-deep storage into account, another probability-based approach is applied. A European material handling provider had given the data used in this publication. Through an example, the influences of the storage policy and the storage depth are depicted.

DSS approach for sustainable system design of shuttle-based storage and retrieval systems

DSS approach for sustainable system design of shuttle-based storage and retrieval systems

A joint optimisation of multi-item order batching and retrieving problem for low-carbon shuttle-based storage and retrieval system

Shuttle-based storage and retrieval system (SBS/RS) is a smart warehouse system evolved from automated storage and retrieval system. It is used for the storage and order picking of products in e-commerce warehouses because of its flexibility and low-carbon feature. This paper investigates the multi-item order batching and retrieving problem for SBS/RS, in which orders containing different items are batched and processed by the system. A mixed-integer linear programming model is proposed to jointly optimise the batching and retrieving assignment, and a tabu search algorithm along with an efficient algorithm for generating retrieving assignments are developed for problem-solving. Numerical experiments are then conducted to validate the efficiency of the proposed algorithm as well as the carbon emission reduction potential of the developed model.

Order dividing optimisation in crane & shuttle-based storage and retrieval system

The crane & shuttle-based storage and retrieval system (C&SBS/RS) is the first automated warehouse technology that supports pallet picking, case picking and item picking. In the C&SBS/RS, aisle-captive cranes perform pallet picking, while tier-captive shuttles handle cases and items picking. To balance picking tasks, we propose an order dividing algorithm to fulfil required specific picking sequences. The optimisation objective is to minimise the order line picking time. Therefore, we modelled and analyzed the C&SBS/RS and considered single and dual command cycles for each resource (i.e. cranes, rail-guided vehicles, shuttles and lifters) separately according to their respective operation processes. Finally, numerical experiments were conducted to analyze impact factors and a real case to verify the power of the proposed order dividing algorithm.