Tandem Automated Guided Vehicle Systems Research Articles

Multi-agent based scheduling method for tandem automated guided vehicle systems

We consider the scheduling method that allows to minimize the traveling time of a AGV (and thus energy consumption) at each of zones, while to minimize the waiting time of the automated guided vehicles (AGVs) and/or containers for pickup and delivery (PD) at the transfer points (TPs) installed between adjacent zones in tandem systems. Scheduling for these tandem AGV systems is often not possible from a single point by a single intelligent agent. Intead, scheduling has to be performed using multiple intelligent agents. We consider the cooperative multi-agent scheduling (CMAS) scheme in which each agent employs a multi-offspring genetic algorithm. Coordination between the agents is used to improve their schedulings. This coordination can be in the form of serial scheme. We propose a novel CMAS method based on Lagrange theory and compare this to a non-cooperative scheduling approach between agents. The proposed method is verified at AGV system for a book printing process in Pyongyang Textbook Print Shop as the real-world experiment and it is shown that the CMAS method for tandem AGV system is effective.

A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem

Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average.

Optimal location of workstations in tandem automated-guided vehicle systems

The way workstations are located in a tandem automated-guided vehicle (AGV) systems affect the total lateness of the system. So far, almost all studies have focused on either minimizing the total flow or minimizing the total AGV transitions in each zone. This study presented a novel approach to locate the workstations in a tandem AGV zones by developing a new mixed-integer programming (MIP) formulation. The objective is to minimize total waiting time of all workstations which is equivalent to minimizing the total lateness of each zone. Lateness is defined as the total idle time of a workstation waiting to be supplied by an AGV. The proposed MIP formulation is very competitive and has the capability to solve instances of up to 25 workstations to optimality in a reasonable amount of time.

A machine-to-loop assignment and layout design methodology for tandem AGV systems with single-load vehicles

In this paper, we propose a method for design of tandem automated guided vehicle (AGV) systems with single-load vehicles. We consider the concurrent design of machines layout and AGV guide paths for a tandem system. Our goal is to devise a method that can achieve the following objectives: (1) maximise the workload balance between loops; (2) minimise the inter-loop flow; and (3) minimise the total flow distance. Our method solves the problem in four stages, considering the machines layout and the tandem paths at the same time. It assigns machines to loops, determines the layout of each loop, arranges loops on the floor, and finally designs a transportation centre to link the loops. We compare the performance of our method with a sequential design method that first determines the layout and then assigns the machines to loops. We solve a number of randomly generated problems for both methods. Results indicate that the proposed algorithm performs faster and achieves lower values of inter-loop flows and inter-loop flow distances.

A new memetic algorithm for optimizing the partitioning problem of tandem AGV systems

In tandem automated guided vehicle (AGV) systems, all the work stations (processing centers) are partitioned into non-overlapping zones, where each zone is served by a dedicated vehicle. Beside the system input/output stations, additional pickup/drop-off (P/D) points are installed to link these zones as transfer points. In this paper, a new memetic algorithm (MA) is proposed to optimize the partitioning problem of tandem AGV systems. MAs are hybrid evolutionary algorithms (EAs) that combine the global and local search by using a genetic algorithm (GA) to perform exploration and a local search method to perform exploitation. Hence, a local search method has been designed and combined with a GA to refine the individuals of the population (i.e. improve their fitness). The objective is to minimize the maximum AGVs’ workload in order to balance the workload among all the zones and hence avoid the presence of bottlenecks. The MA performance is evaluated by comparing the obtained results with the reported results in the literature as well as the pure GA. Furthermore, some newly designed test cases are proposed and solved using both, MA and GA. The results show that, overall, the developed MA outperforms both pure GA and the other reported methods in the literature.

Partitioning machines in tandem AGV systems based on “balanced flow strategy” by simulated annealing

A tandem automated guided vehicle (AGV) system deals with grouping workstations into some non-overlapping areas and assigning to each area exactly one AGV. This paper presents a new non-linear integer mathematical model to group n machines into N loops to minimize both inter-loop and intra-loop flow simultaneously based on balanced-loops strategy and inter-machine flows taken from ideas of cellular manufacturing systems. Due to computational difficulties of exact methods in solving the proposed model, a simulated annealing (SA) algorithm is proposed. A number of test problems are generated at random and solved by the proposed SA in order to show the efficiency of the algorithm. Finally, the results are reported by both the Lingo software and the proposed SA algorithm.

Zones formation algorithm in tandem AGV systems:a comparative study

In tandem automated guided vehicle (AGV) systems, the shop floor is divided into a group of non-overlapping zones, where each zone is served by a single dedicated AGV. In this paper, a partitioning algorithm for designing tandem AGV systems is proposed. The proposed algorithm serves a number of objectives; minimizing the total handling cost, minimizing the maximum workload in the system and minimizing the number of between-zones trips. The algorithm is equipped with parameters to enable the user to select one of these objectives or a combination of them to optimize. It starts by generating candidate zones with a search technique that takes into consideration the chosen objective. Each candidate zone is then checked for integrity and feasibility to ensure that zones are non-overlapping and can bear their imposed workloads. A 0–1 integer programming model is used to select the zones for the final configuration according to the chosen objective function. The performance of the proposed algorithm is evaluated by comparison with other algorithms from literature in solving a group of benchmark problems. The results of the comparison showed that the proposed algorithm outperformed the other algorithms when considering the shortest time to travel first (STTF) empty vehicle dispatching policy.

A machine-to-loop assignment and layout design methodology for tandem AGV systems with multiple-load vehicles

In this paper, we propose a design methodology for tandem Automated Guided Vehicle (AGV) systems with multiple-load vehicles. Our goal is to devise a design methodology that can achieve the following objectives in multiple-load tandem AGV designs. The first objective is to achieve the workload-balance between vehicles of different loops. The second objective is to minimize the inter-loop flow. The final objective is to minimize the flow distance. To achieve these objectives, the following problems are studied. First, we conduct simulations to study the relationship between a vehicle's load-carrying capacity and work capacity. This relationship is then considered in the second problem, i.e. the problem of determining the machine content of each loop. A two-stage machine-to-loop assignment method is proposed for solving this problem. At the first stage, an initial machine-to-loop assignment is generated. This initial assignment is then improved at the second stage using Simulated Annealing (SA). The third problem is the problem of determining the layout of machines in each loop. A flow-line design method and SA are adopted for solving this problem. The fourth problem is the layout problem of guide-path loops. To solve this problem, a famous layout method found in the literature is adopted. The last problem includes the problem of determining the best orientation of each loop and the problem of finding the best places to set up transfer stations between adjacent loops. A mathematical programming model that can solve them simultaneously is proposed. Simulations are then conducted to verify the design, and to show that the proposed design methodology is indeed capable of producing good and satisfactory tandem AGV designs with multiple-load AGVs. Finally, it is our hope that the knowledge learned from this study can help us have a better understanding of multiple-load AGV systems and allow us to have successful implementations of similar systems in practice.

A design for a tandem AGVS with multi-load AGVs

A tandem automated guided vehicle system (AGVS) is obtained by partitioning all workstations into multiple zones and assigning a single vehicle to each zone. In this paper, we propose an analytical model to design a tandem AGVS with multi-load AGVs. Using simulations, the performance of the proposed model is shown by comparing it with a conventional multi-load AGVS.

Design of a variable path tandem layout for automated guided vehicle systems

The partitioning of a tandem layout for an automated guided vehicle (AGV) system directly affects the system performance. Determining the location of the transfer points between zones is another important issue in the design of a tandem layout. In this paper, a heuristic partitioning algorithm for a tandem AGV system based on the concept of variable path routing within a zone is developed. Transfer points are simultaneously determined during the network partitioning process. The algorithm assumes the prior existence of a conventional and unidirectional layout. The problem of interest is one of converting the existing, conventional layout to a variable path based tandem AGV system layout. A comparison between the conventional and the tandem AGV system with respect to system performance under the same operating conditions is presented. The results show that the variable path based tandem layout requires a smaller number of vehicles in most situations than the equivalent conventional layout. In addition, the total vehicle use time of a tandem layout is smaller than that of the conventional layout.

Statistical tolerance analysis based on beta distributions

In an earlier paper, Bozer and Srinivasan introduced the tandem concept for automated guided vehicle (AGV) systems and presented an analytical model to evaluate the throughput performance of a basic component of the system; namely, a single vehicle serving a set of workstations under the First-Encountered-First-Served rule. In this study, using the above analytical model and certain column generation techniques, we present a heuristic partitioning scheme to configure tandem AGV systems. The partitioning scheme is based on a variation of the well-known set partitioning problem. It is aimed at evenly distributing the workload among all the AGVs in the system. We demonstrate the procedure with two numerical examples. Using simulation, the performance of the tandem configuration obtained for each example is compared to that of the corresponding conventional AGV system.

A design process for tandem automated guided vehicle systems: the concurrent design of machine layout and guided vehicle routes in tandem automated guided vehicle systems

Explains that a tandem automated guided vehicle (AGV) system is composed of several non‐overlapping closed loops. Stations or machines within each loop are served by a single dedicated vehicle. The transit area located between two adjacent loops serves as an interface and allows loads to be transferred from one loop to another. If a load needs to be delivered to a machine not located within the same loop, the load will need more than one vehicle to carry it to its destination. Develops a model to solve the machine partition and layout problems concurrently in tandem AGV systems. During the design process, the objective is to minimize the number of loops to reduce the setup costs of AGVs in the system. Naturally, the desirability of a prospective loop must be evaluated in terms of the number of machines it covers, the workload of each AGV, and the ratio of the flow within the loop to the total flow associated with that loop.Quality indicators Research implications** Practice implications** Originality** Readability**

An algorithm for routeing control of a tandem automated guided vehicle system

Abstract A tandem AGV (automated guided vehicle) system is composed of several non-overlapping closed loops. Stations within each loop are served by a single dedicated vehicle. The transit area located between two adjacent loops serves as an interface and allows loads to be transferred from one loop to another. If a load needs to be delivered to a station not located within the same loop, the load needs more than one vehicle to carry it to its destination. We regard this routeing problem as a problem of finding the shortest travel time. After a command to deliver a load is issued, finding a route from the source to the destination as rapidly as possible without disrupting other active travel schedules was the objective of this study. A task-list time-window algorithm to find a shortest travel time based on the current status to route a load from point A to point B is presented. Two idle-vehicle managements are considered: circulating (CIRC) and STAY policies. Experiments showed that the STAY policy is mor...

Performance evaluation of tandem and conventional AGV systems using generalized stochastic Petri nets

Abstract This paper investigates the different policies and concepts followed in the traffic management of automated guided vehicle (AGV) systems, and develops the controls for automatically eliminating potential vehicle conflicts in an AGV system. The planning of the AGV system is performed in such a way that there are no conflicts or deadlocks for the vehicles using stochastic Petri nets (SPNs). The major effort is devoted to determining the benefits of the tandem AGV control in comparison with the conventional AGV control method. SPNs have been used to model the different designs of flexible manufacturing systems (FMSs) and with different policies for the movement of material, vehicle path control, inventory planning and tool control. The SPN model is solved and the performance of the system can be evaluated. In this study, the effort is directed to model an FMS with two different types of AGV traffic management methods, namely the conventional and tandem AGV control. A SPN program is used which takes ...

A load-routeing problem in a tandem-configuration automated guided-vehicle system

Abstract Automated guided vehicles are commonly employed in modern automated material-handling systems or flexible manufacturing systems. A new configuration for an automated guided-vehicle system (AGVS), called a tandem AGVS, has been proposed recently. Efficient use of this configuration is required to solve the load-routeing problem (LRP), a specific operational issue which affects the production system performance. In this paper, LRPs are studied and a two-phase approach is proposed to solve it. Phase 1 consists of an analytical approach based on the steady state. The output of phase 1 provides an adequate estimate and recommendation of routeing decisions of an operational system. Phase 2 is a simulation model which accepts the results from phase 1 to realize the impact of another operational performance such as the queue length of each station. It has been established that the LRP affects the operational performance of the AGVS.

Tandem AGV systems: A partitioning algorithm and performance comparison with conventional AGV systems

In an earlier paper, Bozer and Srinivasan introduced the tandem concept for automated guided vehicle (AGV) systems and presented an analytical model to evaluate the throughput performance of a basic component of the system; namely, a single vehicle serving a set of workstations under the First-Encountered-First-Served rule. In this study, using the above analytical model and certain column generation techniques, we present a heuristic partitioning scheme to configure tandem AGV systems. The partitioning scheme is based on a variation of the well-known set partitioning problem. It is aimed at evenly distributing the workload among all the AGVs in the system. We demonstrate the procedure with two numerical examples. Using simulation, the performance of the tandem configuration obtained for each example is compared to that of the corresponding conventional AGV system.