An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manufacturing industry. In general, an automated guided vehicle (AGV) in the Fab’s AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS’s complexity and uncertainty. Unexpected vehicle congestion increases the delivery time and deteriorates the Fab’s production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab’s AMHS.

The Dynamic Vehicle Routing Problem (DVRP) involves a combinatorial optimization problem where new customer demands become known over time, and old routes must be reconfigured to generate new routes while executing the current solution. We consider the high level of dynamism problem. An application of highly dynamic DVRP is the ambulance service where a patient contacts the service center, followed by an evaluation of case severity, and a visit by a practitioner/ ambulance is scheduled accordingly. This paper considers a variant of the DVRP and proposes a decentralized algorithm in which collaborators (Depot and Vehicle), both have only partial information about the entire system. The DVRP is modeled as a periodic re optimization of VRP using the proposed decentralized algorithm where collaborators exchange local information to achieve the best global objective for the current state of the system. We assume the existence of a dispatcher e.g., headquarter of the company who can communicate to vehicles in order to gather information and assigns the new visits to them. The effectiveness of the proposed decentralized coordination algorithm is further evaluated using benchmark data given in literature. The results show that the proposed method performed better than the compared algorithms which utilize the centralized coordination in 12 out of 21 benchmark problems.

Robot manipulators are highly nonlinear system with multi-inputs multi-outputs, and various control methods for the robot manipulators have been developed to acquire good trajectory tracking performance and improve the system stability lately. The computed torque controller has nonlinear feedforward control elements and so it is very effective to control robot manipulators. If the control gains of the computed torque controller is adjusted according the payload, then more precise control performance is attained. This paper extends the conventional computed torque controller in the joint space to the Cartesian space, and optimize the control gains for some specified payloads in both joint and Cartesian spaces using genetic algorithms. Also a neural network is employed to have proper control gains for arbitrary payloads using generalization properties of the neural network. Computer simulation results show that the proposed control system for robot manipulators has excellent performance in various conditions.

Recently, owing to the development of ICT industry and wide spread of smart phone, the number of people who use car sharing service are increased rapidly. Currently two-way car sharing system with same rental and return locations are mainly operated since this system can be easily implemented and maintained. Currently the demand of one-way car sharing service has increase explosively. But this system have several obstacle in operation, especially, vehicle stock imbalance issues which invoke vehicle relocation. Hence in this study, we present an optimization approach to depot location and relocation policy in one-way car sharing systems. At first, we modelled as mixed-integer programming models whose objective is to maximize the profits of a car sharing organization considering all the revenues and costs involved and several constraints of relocation policy. And to solve this problem efficiently, we proposed a new method based on particle swarm optimization, which is one of powerful meta-heuristic method. The practical usefulness of the approach is illustrated with a case study involving satellite cities in Seoul Metrolitan Area including several candidate area where this kind systems have not been installed yet and already operating area. Our proposed approach produced plausible solutions with rapid computational time and a little deviation from optimal solution obtained by CPLEX Optimizer. Also we can find that particle swarm optimization method can be used as efficient method with various constraints. Hence based on this results, we can grasp a clear insight into the impact of depot location and relocation policy schemes on the profitability of such systems.

가속도를 계측하여 부상력을 제어하는 것은 가장 기본적인 자기부상열차의 부상공극 제어기법이다. 이에 이 연구에서는 가속도 되먹임에 기반한 부상공극제어기법을 자기부상열차에 적용하고, 이를 고려한 자기부상열차-가이드웨이 상호작용계의 동적거동 해석기법을 개발한다. 개발된 해석기법을 사용하여 실제 자기부상열차-가이드웨이 상호작용계의 동적해석을 수행하였다. 해석 결과를 통해 가속도 되먹임에 기반한 부상공극제어기법을 적용하여도 현재까지 제안된 자기부상열차 설계 기준을 충분히 만족함을 확인하였다. 즉, 현재 제안된 자기부상열차 가이드웨이 구조물의 설계 기준을 보완하여 안전하면서도 경제적인 구조물의 건설이 가능해질 것으로 예상된다.

This study focuses on the formation of input release lots in a semiconductor wafer fabrication facility. After the order-lot pegging process assigns lots in the fab to orders and calculates the required quantity of wafers for each product type to meet customers’ orders, the decisions on the formation of input release lots should be made to minimize the production costs of the release lots. Since the number of lots being processed in the wafer fab directly is related to the productivity of the wafer fab, the input lot formation is crucial process to reduce the production costs as well as to improve the efficiency of the wafer fab. Here, the input lot formation occurs before every shift begins in the semiconductor wafer fab. When input quantities (of wafers) for product types are given from results of the order-lot pegging process, lots to be released into the wafer fab should be formed satisfying the lot size requirements. Here, the production cost of a homogeneous lot of the same type of product is less than that of a heterogeneous lot that will be split into the number of lots according to their product types after passing the branch point during the wafer fabrication process. Also, more production cost occurs if a lot becomes more heterogeneous. We developed a multi-dimensional dynamic programming algorithm for the input lot formation problem and showed how to apply the algorithm to solve the problem optimally with an example problem instance. It is necessary to reduce the number of states at each stage in the DP algorithm for practical use. Also, we can apply the proposed DP algorithm together with lot release rules such as CONWIP and UNIFORM.

본 연구의 목적은 가까운 미래의 선박운동정보를 이용하는 피드포워드 제어알고리즘과 FPSO 운동 수치 시뮬레이션 모델을 개발하고 시뮬레이션을 통하여 제어알고리즘의 성능을 검증하는 것이다. 본 논문에서는 조류, 바람, 파력 등의 환경하중에 의하여 발생한 선체운동의 미래 예측치를 활용한 피드포워드 제어력을 추가적으로 가지는 Dynamic Positioning System에 대하여 연구한다. 먼저, 조류력, 풍력 및 파력에 대한 수학모델을 선정하여 환경하중에서의 선체운동을 계산하고, 현재의 선체운동 값과 Brown 지수평활 예측모형을 활용하여 미래 선체운동 값을 예측하였다. 또한 위치 유지와 Heading angle 제어를 위한 제어력을 PID(Proportional-Integral-Derivative)이론을 이용하여 결정한 피드백 제어기와 미래 선체운동 값을 이용하여 결정한 피드포워드 제어기로 구성하였다. 그리고 각 Thruster에 요구되는 추력은 라그랑지승수법을 활용하여 분배하였다. 마지막으로 FPSO(Floating Production Storage and Offloading)의 운동과 Dynamic Positioning System에 대한 시뮬레이션 모델을 구축하여 선박의 위치 및 Heading angle 제어에 관한 시뮬레이션을 수행하여 제안하는 피드백 제어기와 피드포워드 제어기를 동시에 가지는 제어시스템의 성능을 평가하였다. 본 연구의 결과, 피드백 및 피드 포워드 제어기가 적용된 DPS 제어시스템이 기존의 피드백 제어기보다 위치유지 및 헤딩각 유지 능력에서 개선되었고 각 Thruster에 요구되는 평균 제어력 및 최대 제어력의 크기도 감소함을 보였다. 이에 따라 DPS에 요구되는 동력 감축과 Azimuth Thruster 용량의 감소로 인하여 비용 절감의 효과를 기대할 수 있다.

This study develops a dynamic scheduling model for parallel machine scheduling problem based on genetic algorithm (GA). GA combined with discrete event simulation to minimize the makespan and verifies the effectiveness of the developed model. This research consists of two stages. In the first stage, work sequence will be generated using GA, and the second stage developed work schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlapping work, which causes bottleneck and long lead time. If not, go back to the first stage and develop another schedule until satisfied. Small size problem was experimented and suggested a reasonable schedule within limited resources. As a result of this research, work efficiency is increased, cycle time is decreased, and due date is satisfied within existed resources.

MLS(Moving Least Squares) 차분법은 무요소법의 이동최소제곱법과 Taylor 전개를 이용하여 요소망의 제약 및 수치 적분이 없이 절점만을 이용하여 미분방정식을 수치해석할 수 있는 방법이다. 본 연구에서는 고체역학 문제의 동적해석을 위하여 MLS 차분법의 시간이력해석 알고리즘을 제시한다. 개발된 알고리즘은 Newmark 방법으로 시간적분을 하였으며, 강형식을 그대로 이산화하여 해석을 수행했다. 이동최소제곱법을 이용해 Taylor 전개식을 근사하여 실제 미분계산없이 미 분근사식을 얻기 때문에 고차까지 Taylor 다항식의 차수를 증가하는 것이 용이하다. 1차원과 2차원 수치예제들을 통하여 동적해석을 위한 MLS 차분법의 정확성과 효율성을 검증하였다. 수치결과들이 정확해에 잘 수렴하였으며, 유한요소법 (FEM)의 해석결과와 비교하여 떨림현상(oscillation) 및 주기성(periodicity) 오차에 대해 보다 안정적인 모습을 보였다.

본 논문에서는 동적계획법과 계층적 변이추적을 이용한 새로운 스테레오 정합 알고리즘을 제안 한다. 기존 동적계획법을 이용한 정합 알고리즘에서는 밝기 변화가 적거나 폐색영역과 같은 정합 화소 의 부재 등으로 인하여 정합 오류를 동반하므로 생성된 변이 맵을 신뢰할 수 없는 문제를 갖는다. 그러 므로 제안한 방법에서는 계층간의 변이 추적기법을 도입하여 이러한 정합 오류를 복원할 수 있도록 알 고리즘을 구성하였다. 입력된 스테레오 영상을 부 표본화를 통해 계층화 하고 동적계획법을 이용하여 생성된 각 계층의 변이 맵으로부터 계층사이의 변이 이동오차와 밝기에 기반한 정합오차를 계산하여 정합 오류를 줄임으로써 보다 정확한 변이를 선택하도록 하였다. 실험 결과에서 보듯이 밝기 변화가 적은 영역과 폐색영역 등에서 기존의 동적계획법방법 보다 개선된 성능을 보였다.

Wireless LAN systems have been widely implemented for supporting the sireless internet services especially in the hotspot areas such as hospitals, homes, conference rooms, and so on. Compared with wired LAN systems, wireless LAN systems have the advantage

This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of v

Broadband networks are designed to support a wide variety of services with different traffic characteristics and demands for Quality of Services. Bandwidth allocation methods can be classified into two major categories： static and dynamic. In static allocation, bandwidth is allocated only at call setup time and the allocated bandwidth is maintained during a session. In dynamic allocation, the allocated bandwidth is negotiated during a session. The purpose of this paper is to develop policies for deciding and for adjusting the amount of bandwidth requested for a best effort connection over such as ATM networks.. This method is to develop such policies that a good trade off between utilization and latency using cell delay variation to the forecast the incoming traffic in the next period. The performances of the different polices are compared by simulations.

Broadband networks are designed to support a wide variety of services with different traffic characteristics and demands for Quality of Services. Bandwidth allocation methods can be classified into two major categories: static and dynamic. In static allocation, bandwidth is allocated only at call setup time and the allocated bandwidth is maintained during a session. In dynamic allocation, the allocated bandwidth is negotiated during a session. The purpose of this paper is to develop policies for deciding and for adjusting the amount of bandwidth requested for a best effort connection over such as ATM networks. This method is to develop such policies that a good trade off between utilization and latency using cell delay variation to the forecast the incoming traffic in the next period. The performances of the different polices are compared by simulations.

구조물의 동적해석의 주된 관점은 적은 갯수의 모우드형상과 계산과정으로 적정정도의 해를 구하는 것이다. Component mode method는 부분구조물 기법을 이용하여 자유도를 줄이는 방법을 이용하였으나 동하중의 특성이 고려되지 않는 단점이 있으며 이를 보완하기 위한 Ritz Vector법은 많은 반복연산이 필요하며 오차가 가중되는 단점이 있다. 본 연구에서는 Component mode method의 효율성을 개선시키고자 기존의 장점을 유지하면서 직접적분과정에서의 계산량을 현저히 줄일 수 있는 Lanczos 알고리즘을 도입하였다. 이 방법의 효율성을 검증하기 위하여 예제구조물을 해석하여 SAP90의 결과와 비교하였다.

The main intention of this paper is to develop and compare the algorithm based on finite element procedures for nonlinear transient dynamic analysis which has combined effects of material and geometric nonlinearities. Incremental equilibrium equations based on the principle of virtual work are derived by the finite element approach. For the elasto - plastic large deformation analysis of shells and the determination of the displacement-time configuration under time-varying loads, the explicit, implicit and combined explicit-implicit time integration algorithm is adopted. In the time structure is selected and the results are compared with each others. Isoparametric 8-noded quadrilateral curved elements are used for shell structure in the analysis and for geometrically nonlinear elastic behaviour, a total Lagrangian coordinate system was adopted. On the other hands, material nonlinearity is based on elasto-plastic models with Von-Mises yield criteria. Thus, the combined explicit-implicit time integration algorithm is benefit in general case of shell structure, which is the result of this paper.

동적해석에 대한 최근의 연구는 구조물의 자유도보다 적은 모우드 형상들을 사용하여 구조물을 해석하는 효과적인 방법을 찾는데 있다. Ritz알고리즘과 모우드가속도법은 모우드중첩법을 개선하고자 개발되었는데, Ritz알고리즘은 하중의 공간적 특성을 포함하지만, 계산과정에서 유용한 직교성을 잃는 경향이 있으며, 모우드가속도법은 만족할 만한 해를 얻기 위해 많은 수의 모우드 형상들을 고려해야 하는 단점이 있다. 또한 앞의 두 방법을 조합한 방법이 개발되었으나 너무 많은 계산과정과 시간을 필요로 한다. 이 연구의 목적은 Lanczos알고리즘을 이용하여 Ritz알고리즘의 효율성과 정확성을 보완하고 이를 프로그램화하여 검증하는데 있다. 본 연구의 결과로부터 Modified Ritz알고리즘을 이용한 동적해석방법이 합리적임이 증명되었다.