Route planning for automated guided vehicles in a manufacturing facility

Automated guided vehicles (AGVs) are widely used in manufacturing and transporting facilities for the movement of material from one location to another. Research in this area is directed toward the development of a path layout design and routing algorithms for movements of materials. The problem is to design a path layout and a routing algorithm that will route the AGVs along the bi-directional path so that the distance travelled will be minimized. This paper presents a bi-directional path flow layout and a routing algorithm that guarantee conflict-free, shortest-time routes for AGVs. Based on the path layout, a routing algorithm and sufficient, but necessary, conditions, mathematical relationships are developed among certain key parameters of vehicle and path. A high degree of concurrency is achieved in vehicle movement. Routing efficiency is analysed in terms of the distance travelled and the time required for AGVs to complete all pickup and drop-off jobs. Numerical results are presented to compare the performance of the proposed model. The research provides the foundation for a bi-directional path layout design and routing algorithms that will aid the designer to develop complicated path layouts.     

Scheduling and routing algorithms for AGVs: A survey

Automated guided vehicles (AGVs) are now becoming popular in automated materials handling systems, flexible manufacturing systems and even container handling applications. In the past few decades, much research has been devoted to the technology of AGV systems and rapid progress has been witnessed. As one of the enabling technologies, scheduling and routing of AGVs have attracted considerable attention. Many algorithms for the scheduling and routing of AGVs have been proposed. However, most of the existing results are applicable to systems with a small number of AGVs, offering a low degree of concurrency. With a drastically increased number of AGVs in recent applications (e.g. in the order of a hundred in a container handling system), efficient algorithms are needed to resolve the increased contention of resources (e.g. path, loading and unloading buffers) among AGVs. This survey paper first gives an account of the emergence of the problem of AGV scheduling and routing. It then differentiates it from several related problems and classifies major existing algorithms for the problem. Finally, the paper points out fertile areas for future study of AGV scheduling and routing.     

A neural algorithm for finding the shortest flow path for an automated guided vehicle system

The automated guided vehicle (AGV)system is emerging as the dominant technology to maximize the flexibility of material handling, while increasing the overall productivity of manufacturing operations. This paper presents a new way of finding the shortest flow path for an AGV system on a specific routing structure. An optimal solution of the system is determined by using an approach based on the Hopfield neural network with the simulated annealing (SA) procedure. In other words, the proposed approach reduces the total cost of an AGV delivery path from one workstation to another on the shop floor. By changing the temperature of the two-stage SA, a solution can be found that avoids potential collisions between AGVs. Both the flow path and the potential collision, which are major problems in AGV systems, may be solved simultaneously by the proposed neural network approach. Other advantages offered by the proposed method are its simplicity compared with operations research (OR)methods and a decreased number of needed AGVs. The performance of the approach is also investigated.     

基于路段时间窗考虑备选路径的AGV路径规划

针对自动化集装箱码头基于卸箱任务的自动导引车（automated guided vehicle,AGV）路径规划问题,结合最优路径数学模型、路径搜索方法和时间窗,提出了一种基于路段时间窗的AGV路径规划方法。首先,在给AGV下派任务的基础上,用最优路径数学模型为AGV规划出最短路径;其次,用路径搜索方法搜索AGV的备选路径,在路径长度相同的情况下,按照路径中转折次数确定备选路径优先级,转折次数少的备选路径优先级高;最后,在各AGV最短路径下,设置各个路段的时间窗,时间窗无重叠则表明AGV无冲突,对于时间窗重叠的路段,采用在原路径上插入时间窗或者在备选路径上插入时间窗的方法,再进行时间窗重叠测试,若还存在重叠的,则继续调整至最终实现多AGV的无冲突路径规划。为了验证方法的有效性,以8台AGV分区同时工作为例,用实例证明所提出的路径规划方法的避碰效果。结果显示该方法能为多台同时工作的AGV规划出一条无冲突优化路径,并且用时较短;在试验中发现选择在备选路径上插入时间窗的方法效果更好。研究表明所提方法能有效实现AGV的避碰,提高AGV利用率和自动化集装箱码头的运作效率。     

考虑冲突避免的多AGV路径规划研究

目的 提高物流企业“货到人”拣选系统在实际生产中的工作效率，避免自动导引小车(AGV)间的冲突死锁，研究大规模多AGV的无冲突路径规划和协同避障问题。方法 首先考虑AGV空载、负载情况和路径扩展成本，改进A^*算法，动态调整代价函数，优化路径扩展方式。其次，提出冲突检测及避免算法，对可能产生局部冲突的路径交叉点进行避障调度，通过预约锁格，实现局部冲突的检测，制定优先级避障策略，解决AGV动态行驶路径上产生的局部冲突和死锁，进而实现全局无冲突路径规划。结果 对多组不同任务量和不同AGV规模的场景进行仿真，实验结果表明，考虑冲突避免的改进A^*算法能有效实现100个任务、90个货架单位和7个拣选站场景下的多AGV动态路径规划，相较于传统A^*算法，其平均拣选时长缩短了52.61%。结论 该方法可实现大规模场景下的多AGV动态路径规划，在付出较小转弯代价的同时有效避免局部动态冲突，该方法可为相关企业实现多AGV协同调度提供新的思路和理论依据。     

Deadlock prevention for automated guided vehicles in automated container terminals

Automated guided vehicles (AGVs) are an important component for automating container terminals. When utilizing AGVs to transport containers from one position to another in a container terminal, deadlocks are a serious problem that must be solved before real operations can take place. This study assumes that the traveling area for AGVs is divided into a large number of grid-blocks, and, as a method of traffic control, grid-blocks are reserved in advance when AGVs are running. The first purpose of the reservation is to make room between AGVs and to prevent deadlocks. The objective of this study is to develop an efficient deadlock prediction and prevention algorithm for AGV systems in automated container terminals. Because the size of an AGV is much larger than the size of a grid-block on a guide path, this study assumes that an AGV may occupy more than one grid-block at a time. This study proposes a method for reserving grid-blocks in advance to prevent deadlocks. A graphical representation method is suggested for a reservation schedule and a priority table is suggested to maintain priority consistency among grid-blocks. It is shown that the priority consistency guarantees deadlock-free reservation schedules for AGVs to cross the same area at the same time. The proposed method was tested in a simulation study.     

基于动态时间窗的泊车系统路径规划研究

针对智能立体停车库中自动导引运输车(automated guided vehicle,AGV)存取车路径规划问题,采用分时利用策略,将Dijkstra算法和时间窗法有效结合,提出了一种基于动态时间窗的泊车系统路径规划方法。首先,通过引入优先级策略为接收任务的AGV设定优先级;其次,采用Dijkstra算法,按照任务优先级高低次序,依次为接受任务的AGV规划出最短可行路径;最后,在已知AGV可行路径基础上,通过对可行路径各路段的时间窗进行初始化、实时更新以及实时排布处理,实现多AGV的无冲突路径规划。为验证所提方法的可行性和有效性,以4台AGV同时工作的智能立体停车库为实例进行仿真测试。结果显示:所提出的路径规划方法不仅有效解决了目前多AGV路径规划柔性差、易出现死锁、碰撞冲突等问题,而且可在有效解决路径冲突的前提下,为接受任务的AGV规划出一条时间最短的优化路径。所提方法具有较好的鲁棒性和柔性,有效提高了智能立体停车系统整体运行效率,降低了存取车等待时间。     

Scheduling vehicles in automated transportation systems Algorithms and case study

One of the major planning issues in large scale automated transportation systems is so-called empty vehicle management, the timely supply of vehicles to terminals in order to reduce cargo waiting times. Motivated by a Dutch pilot project on an underground cargo transportation system using Automated Guided Vehicles (AGVs), we developed several rules and algorithms for empty vehicle management, varying from trivial First-Come, First-Served (FCFS) via look-ahead rules to integral planning. For our application, we focus on attaining customer service levels in the presence of varying order priorities, taking into account resource capacities and the relation to other planning decisions, such as terminal management. We show how the various rules are embedded in a framework for logistics control of automated transportation networks. Using simulation, the planning options are evaluated on their performance in terms of customer service levels, AGV requirements and empty travel distances. Based on our experiments, we conclude that look-ahead rules have significant advantages above FCFS. A more advanced so-called serial scheduling method outperforms the look-ahead rules if the peak demand quickly moves amongst routes in the system. Received: June 21, 2000 / Accepted: January 22, 2001     

A practical heuristic for the group technology economic lot scheduling problem

Automated Guided Vehicle (AGV) systems are complex to design and to implement. Inefficiencies become difficult to avoid or even to control. This paper presents the theory behind a novel agent based AGV controller that aims to control the flow of AGVs in an effective manner and, therefore, overcome the inefficiencies that can be found in complex designs. Agents are simple entities that interact with other agents to produce an emergent behaviour that is not explicitly programmed into them. The AGV controller presented uses agents as traffic managers to allow access to points and segments in the guide path. Each agent has a rule base that it uses to assess the enquiries that it receives from an AGV. Each enquiry is evaluated only at the smallest possible part of the guide path rather than the entire guide path. AGVs are then able to allocate segments and points on their paths depending on the result of each enquiry. Simulation experiments were used to test the controller and an overview is presented.     

Conflict resolution in AGV systems

Currently, conflict-free routing in AGV systems is established by means of one of the following three approaches: (i) the problem elimination through the adoption of a segmented path flow or tandem queue configuration; (ii) the identification of imminent collisions through forward sensing and their aversion through vehicle backtracking and/or rerouting; or (iii) the imposition of zone control and extensive route pre-planning, typically based on deterministic timing of the vehicle traveling and docking stages. Among these three approaches, the segmented path flow-based approach presents the highest robustness to the system stochas-ticities/randomness, but at the cost of restricted vehicle routings and the need for complicated handling operations. This paper proposes an alternative conflict resolution strategy that will ensure robust AGV conflict resolution, while maintaining the operational flexibility provided by free vehicle travel on arbitrarily structured guidepath networks. Specifically, the approach advocated in this paper also employs zone control, but it determines vehicle routes incrementally, one zone at a time. Routing decisions are the result of a sequence of safety and performance considerations, with the former being primarily based on structural/logical rather than timing aspects of the system behavior. The resulting control problem is characterized as the AGV structural control. After defining the notion of AGV structural control, the paper proceeds to the formal characterization and analysis of the problem, and to the development of a structural control policy appropriate for the class of AGV resource allocation systems. The paper concludes with some discussion on the accommodation of emerging AGV operational features in the proposed modeling and analysis framework, and the integration of AGV structural control with the broader control of material-flow among the shop-floor workstations.     

Developing exact and Tabu search algorithms for simultaneously determining AGV loop and P/D stations in single loop systems

There are some issues which have to be addressed when designing an automated guided vehicles system (AGVS) such as flow-path layout, traffic management, the number and the location of pick up and delivery points, vehicle routing and so on. One of the AGVS guide path configurations discussed in the previous researches includes a single-loop which is the subject of this paper. In unidirectional single loop systems, determining the loop for the motion of an AGV, and the location of pick up and delivery (P/D) stations in the cells, are prominent points which, when considered simultaneously, lead to better results than determining each one independently. However, in the literature it is proved that the problem of separately determining the shortest feasible loop is a NP-complete problem. In this paper, by considering a from-to chart and a block layout as the input of problem, we try to determine: (1) a single loop, with at least one shared edge with each cell, (2) the direction of the flow and (3) the location of P/D stations on the loop, all at the same time, in a way that the total travel distance on the loop be minimised. In this regard, first a new exact algorithm is presented and then three heuristic algorithms are developed utilising a Tabu search (TS) method. Solving randomly generated test problems shows that our exact algorithm is capable of solving small size problems; also all three TS algorithms work efficiently in solving problems that could not be solved by exact algorithms.     

An AGV routing policy reflecting the current and future state of semiconductor and LCD production lines

This paper presents an efficient policy for AGV and part routing in semiconductor and LCD production bays using information on the future state of systems where AGVs play a central role in material handling. These highly informative systems maintain a great deal of information on current and near-future status, such as the arrival and operation completion times of parts, thereby enabling a new approach for production shop control. Efficient control of AGVs is vital in semiconductor and LCD plants because AGV systems often limit the total production capacity of these very expensive plants. With the proposed procedure, the cell controller records the future events chronologically and uses this information to determine the destination and source of parts between the parts' operation machine and temporary storage. It is shown by simulation that the new control policy reduces AGV requirements and flow time of parts.     

Comparative analysis of different routing heuristics for the battery management of automated guided vehicles

This paper explores how different routing techniques for the battery management of automated guided vehicles (AGVs) can affect the performance of a system. Four heuristics available in the literature were the basis of this study. Simulation models were developed to investigate how the routing of an AGV towards a battery station can affect the productivity of a manufacturing facility. Results show that the best productivity can be achieved when a routing heuristic tries to jointly minimise the total travel distance and waiting time at a battery station. The gain in productivity, when compared with the highest possible gain theoretically achievable, is quite substantial. It was also found that higher frequency of decision-making (i.e. decisions with smaller time interval) about battery swapping helps to increase the productivity of a system.     

RMS中工件路径网络生成方法

利用图论建立RMS中工件路径网络生成模型。给出设备物理布局生成的3种算法：设备物理规划布局算法、基于二次布置问题(QAP)模型的VMC设备物理布局算法以及已有设备物理布局算法。给出AGV路径网络生成算法、AGV路径网络生成改进算法、可替代路径网络生成算法,包括节点间最短路径寻找子算法、路径网络预处理子算法。算法的输入为表示重构对象节点间距离信息的距离矩阵文件和表示某生产周期多工艺路线的流量文件,输出为优化的路径网络。用Visual C 实现了以上算法,实例测试验证了算法的正确性。     

Simulation-based performance evaluation of transport vehicles at automated container terminals

Significant unproductive and costly waiting occurs during AGV (Automated Guided Vehicle) use, both under the CC (Container Crane) and in the blocks compared to that of a manual yard tractor. A possible solution to this problem is that, in the design of ACT (Automated Container Terminals), ALV (Automated Lifting Vehicles), which can load and unload their own containers, be considered as an alternative. In this paper, the objective is to analyze how increases in the use of ALVs rather than AGVs affects the productivity of ACTs. We derived four inferences regarding the cycle time of vehicles and verified their validity in a simulation. A simulation model of an ACT with perpendicular layout was developed and is described in this paper. From the results of the simulation analysis, we determined the savings effect by cycle time and the required number of vehicles. We demonstrated that the ALV is superior to the AGV in both productivity and efficiency principally because the ALV eliminates the waiting time in the buffer zone.Correspondence to: Yong Seok Choi:     

Heuristic,storage space minimization methods for facility layouts served by looped AGV systems

An analytical method for predicting work-in-process storage requirements resulting from a fixed number of looping, automated guided vehicles (AGVs) serving a line layout is described. The method is based on a model of storage queue dynamics that predicts material flow rates and vehicle response times resulting from vehicle dispatching within a single loop system. The method is applied in the development of two heuristic, random number driven procedures designed to perform sequential search for WIP storage minimizing line layouts over alternative AGV fleet sizes. The first algorithm is a greedy, ‘CRAFT like’ procedure based on local improvement in storage requirements using random, pairwise exchanges of workcentre locations. The second algorithm is a modification to the greedy procedure using simulated annealing methods designed to avoid trapping at local minima. Limited computational studies using the methods are reported.     

Determination of optimal AGV fleet size for an FMS

The required number of AGVs necessary to perform a given level of material handling task in an FMS environment is determined using analytical and simulation modelling. The analytical method involves consideration of load handling time, empty travel time, and waiting and blocking time. Load handling time is computed from given system parameters. Determination of empty vehicle travel is difficult due to the inherent randomness of an FMS. Several research studies for this purpose are discussed and a new model is proposed. It entails formulation of a mixed integer programme with an objective of minimizing empty trips. The constraints are in the form of upper and lower bounds placed on the total number of empty trips starting from or ending at a load transfer station. The phenomena of vehicle waiting and blocking are also discussed. The cumulative impact of these three time estimates are then translated into an initial estimate of AGV fleet size as predicted by individual models. The method is applied to an illustrative example. Finally, simulation methodology is used to validate the initial estimates of fleet size. The results indicate that the different models either under-estimate or over-estimate the actual number of vehicles required in the system. The proposed model, though under-estimates the minimum AGV requirement, yet provides results which are close to the simulation results. Hence, it can be used as an analytical tool prior to the simulation phase of AGVS design.     

An heuristic for configuring a mixed uni/bidirectional flow path for an AGV system

An heuristic methodology has been developed in the present work for configuring a mixed (hybrid) uni/bidirectional flow path for an AGV material handling system. The given unidirectional flow path layout, material flow intensities and vehicle travelling time matrix among various processing centres are taken as input information to this technique. A multiplicative function of material flow intensities between any two centres is used as a criterion for selectively configuring a path as a bidirectional one. The highest such product indicates that the shorter path between that pair of centres is a strong candidate for being configured as bidirectional. The heuristic has been applied to an illustrative FMS and various alternate flow path designs have been obtained. Simulation is then performed with the aim of comparing the productive potentials of the facility when it is operated on either unidirectional, or mixed uni/bidirectional, or allbidirectional flow path design alternatives. The benefits of bidirectional flows over unidirectional counterpart are significant in terms of system throughput rates and optimal AGV fleet sizes. However, traffic control becomes an important issue as vehicle interference and blocking increases with increase in bidirectionality in the network. The decision related to location and capacity planning of vehicle buffering zones is also addressed.     

Strategies for dispatching AGVs at automated seaport container terminals

Control of logistics operations at container terminals is an extremely complex task, especially if automated guided vehicles (AGVs) are employed. In AGV dispatching, the stochastic nature of the handling systems must be taken into account. For instance, handling times of quay and stacking cranes as well as release times of transportation orders are not exactly known in advance. We present a simulation study of AGV dispatching strategies in a seaport container terminal, where AGVs can be used in single or dual-carrier mode. The latter allows transporting two small-sized (20 ft) or one large-sized (40 ft) container at a time, while in single-mode only one container is loaded onto the AGV irrespective of the size of the container. In our investigation, a typical on-line dispatching strategy adopted from flexible manufacturing systems is compared with a more sophisticated, pattern-based off-line heuristic. The performance of the dispatching strategies is evaluated using a scalable simulation model. The design of the experimental study reflects conditions which are typical of a real automated terminal environment. Major experimental factors are the size of the terminal and the degree of stochastic variations. Results of the simulation study reveal that the pattern-based off-line heuristic proposed by the authors clearly outperforms its on-line counterpart. For the most realistic scenario investigated, a deviation from a lower bound of less than 5% is achieved when the dual-load capability of the AGVs is utilized.     

Tandem Configurations for Automated Guided Vehicle Systems and the Analysis of Single Vehicle Loops

Automated Guided Vehicle (AGV) systems continue to play a significant role in many low to medium flow manufacturing operations, including Flexible Manufacturing Systems (FMS) and other applications. The relatively inexpensive guidepath, coupled with the high degree of flexibility and control offered in vehicle routing, has made AGV systems a proven and viable handling technology for the 90's.

Traditionally, AGV systems have been implemented and analyzed assuming that every vehicle is allowed to visit any pick up/deposit point in the system. We introduce a conceptually simple and intuitive approach where the system is decomposed into non-overlapping, single-vehicle loops operating in tandem. In this paper, we also develop an analytical model to study the throughput performance of a single vehicle loop. The resulting expressions are the first closed form analytical expressions that have been obtained to determine the throughput capacity of a single vehicle operating under a specific dispatching rule in a non-deterministic environment.