• Korean Management Science Review
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• v.11 no.1
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• pp.23-37
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• 1994

This paper discusses the methodology for the operational performance of unit-load automated guided vehicles(AGVs) in a flow-shop-type flexible machining and assembly systems (FM/AS). Throughout the paper, AGVs are working as a carrier and mobile workstation. For a double-loop FM/AS, in which one loop is dedicated to machining and the other to assembly, three AGV operating strategies are proposed. Considering the entering interval and travel time of AGVs between workcenters, the strategies are developed to determine the best job sequence which minimizes the makespan and vehicle idle time. Entering times of AGVs and the required minimum number of AGVs are obtained on the basis of the best job sequence. When the number of AGVs are limited, entering times of AGVs are adjusted to maximize the utilization of AGVs.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.299-299
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• 2000

In this paper, a determination method of number of AGVs fer introducing to the multi-path material handling systems is presented by using genetic algorithm. For serving the raw material to each work stations automatically, there needs to introduce a AGVs for transfer the raw martial. To reduce the overall production cost in the material handling systems, however, a trade off exists between the amount of inventory hold on the shop floor and the number of AGVs needed to provide adequate service. In this paper, firstly a objective function which included the net present fixed costs of each stations and each purchased AGVs, delivering cost. stock inventory cost, and safety stock inventory cost is presented. Secondly by using genetic algorithm, the optimal reorder quantity at each stations is decided, where the number of AGVs is increased step by step. From a simulation with different GA parameters, we can determine a optimal number of AGVs to reduce the overall production cost. Thus, the effectiveness of GA for determining the number of AGVs is verified in automated material handling systems.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.109-115
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• 1991

In automated manufacturing systems, Automated Guided Vehicle(AGV) Systems are increasingly important in material handling and manufacturing operations. A considerably flexible AGV system needs to be operated with maximum effectiveness. This paper develops an algorithm for the determination of the entering point and the number of AGVs required in the Flow Shop Type FMS. We consider an AGV used as a carrier and mobile workstation. For the limited number of AGV, the entering point of an AGV on a simple loop is determined in order to maximize the utilization of AGVs. For the unlimited number of AGVs, the number of AGVs required in the FMS is determined on the basis of the entering point of AGVs. The result by the algorithm may be used as a criterion on the control of material flow and the assignment of AGVs in the FMS. A numerical example is given to illustrate the algorithm.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.124-127
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• 1997

A key element in the control of Automated Guided Vehicle Systems (AGVS) is dispatching policy. This paper proposes a new dispatching algorithm for an efficient operation of AGVS. Based on an evolutionary operation, it has an adaptive control capability responding to changes of the system environment. The performance of the algorithm is compared with some well-known dispatching rules in terms of the system throughput through simulation. Sensitivity analysis is carried out varying the buffer capacity and the number of AGVS.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.59-65
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• 1990

In the design of AGVS (Automated Guided Vehicle Systems), one of the important problem is to determine the number of AGVs required to provide a given level of transport service. At present, there are two kind of methods to determine the number of AGVs, the one is to use the mathematical model, the other is to use the simulation technique. Among these, simulation based technique is more reliable than analytical method. In this sense, this paper intend to determine the optimal number of AGVs using personal computer simulation by SIMAN Ver.3.5.

• Management Science and Financial Engineering
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• v.6 no.2
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• pp.47-67
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• 2000

It is discussed how to assign delivery tasks to automated guided vehicles (AGVs) for multiple container cranes in automated container terminals. The primary goal of dispatching AGVs is to complete all the lading and discharging operations as early as possible, and the secondary goal is to minimize the total travel distance of AGVs. It is assumed that AGVs are not dedicated to a specific container crane but shared among multiple cranes. A mathematical formulation is developed and a heuristic algorithm is suggested to obtain a near optimal solution with a reasonable amount of computational time. The single-cycle and the dual-cycle operations in both the seaside and the landside operations are analyzed. The effects of pooling AGVs for multiple container cranes on the performance of an entire AGV system are also analyze through a numerical experiment.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.91-103
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• 2008

In order to simulate the behavior of automated manufacturing systems, the performance of material handling systems should be measured dynamically. Multi-Agent technology could be well adapted for the development of simulator for distributed and intelligent manufacture systems. A multi-agent system is composed of one coordination agent and multiple application agents. Issues in AGVS simulator can be classified by the set-up and operating problems. Decisions on the number of vehicles, bi- or uni-directional guide-path, etc. are fallen into the set-up problem category, while deadlock tree algorithm and conflict resolution are in operating problem. In this paper, a multi-agent based deadlock-free simulator for automated guided vehicle system(AGVS) are proposed through the use of multi-agent technologies and the development of deadlock-free algorithm. In this AGVS simulator proposed, well-known Floyd algorithm is used to create AGVS Guide path, through which AGVS move. Also, AGVs avoid vehicle conflict and deadlock using check path algorithm. And Moving vehicle agents are operated in real-time control by coordination agent. AGV position is dynamically calculated based on the concept of rolling time horizon. Simulator receives and presents operating information of vehicle in AGVS Gaunt chart. The performance of the proposed algorithm and developed simulator based on multi-agent are validated through set of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.795-802
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• 2002

We present a new dynamic routing scheme for multiple autonomous guided vehicles (AGVs) systems. There have been so many results concerned with scheduling and routing of multiple AGV systems; however, most of them are only applicable to systems with a small number of AGVs under a low degree of concurrency. With an increased number of AGVs in recent applications, these AGV systems are faced with another problem that has never been occurred in a system with a small number AGVs. This is the stop propagation problem. That is, if a leading AGV stops then all the following AGVs must stop to avoid any collision. In order to resolve this problem, we propose a nonstop preferential detour (NPD) algorithm which is a new dynamic routing scheme employing an election algorithm. For real time computation, we introduce two stage control scheme and propose a new path searching scheme, k-via shortest path scheme for an efficient dynamic routing algorithm. Finally, the proposed new dynamic routing scheme is illustrated by an example.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.85-94
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• 2008

Automated Guided Vehicles (AGVs) are important equipment in automated container terminals. To utilize AGVs for transporting containers from a position to another, the deadlock is a serious problem that must be solved before they are deployed to real operations. This study assumes that traveling area for AGVs are divided into a large number of grid-blocks and, as a method of traffic control, grid-blocks are reserved in advance during the travel of AGVs. The purposes of the reservation are to make the room between AGVs and to prevent deadlocks. Because the size of an AGV is much larger than the size of a grid-block on guide paths, this study assumes an AGV may occupy more than one grid-block at the same time. This study suggests a method for constructing a table of reservation schedules by using a simulation. A sensitivity analysis was conducted to evaluate the performance of the reservation method in this study.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.591-595
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• 2010

In this paper, a method that dynamically adapts the traffic flow of automated guided vehicles (AGVs) used in automated container terminals to the changing operational condition is presented. In a container terminal, the AGVs are vulnerable to traffic congestion because a large number of AGVs operate in a limited area. In addition, dynamically changing operational condition requires the traffic flow of AGVs to be continuously adjusted to keep up with the change. The proposed method utilizes a genetic algorithm to optimize the traffic flow. Exploiting the dynamic nature of the problem an approach that reuses the results of the previous search is tried to speed up the convergence of the genetic algorithm. The results of simulation experiments show the efficiency of the proposed method.