• Industrial Engineering and Management Systems
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• 제10권3호
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권4호
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• pp.398-408
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• 2016

Based on non-completely hybrid flow line scheduling of panel block in shipbuilding, several uncertain factors influencing the problem were analyzed in a real environment, and a nonlinear integer programming model was built for each sub-scheduling problem. To narrow the difference between theory and application, rolling horizon and rescheduling methods are proposed. Moreover, with respect to the uncertainty of processing time, arriving time and due time, we take the minimizing of the early and delayed delivery costs as the objective, and establish an evaluation with a global penalty function. Finally, numerical experiments and a simulation analysis were undertaken to demonstrate the effectiveness of the model and algorithm.

• 산업공학
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• 제20권3호
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• pp.277-287
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• 2007

Semiconductor manufacturing is one of the most complex and capital-intensive processes composed of several hundreds of operations. In today’s competitive business environments, it is more important than ever before to manage manufacturing process effectively to achieve better performances in terms of customer satisfaction and productivity than those of competitors. So, many semiconductor manufacturing companies implement advanced planning and scheduling (APS) system as a management tool for the complex semiconductor manufacturing process. In this study, we explain roles of production planning and scheduling in semiconductor manufacturing and principal factors that make the production planning and scheduling more difficult. We describe the APS system implementation project at Korean semiconductor manufacturing company in terms of key issues with realistic samples.

• Journal of Information Processing Systems
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• 제5권2호
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• pp.87-96
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• 2009

Grid computing is a new technology which involves efforts to create a huge source of processing power by connecting computational resources throughout the world. The key issue of such environments is their resource allocation and the appropriate job scheduling strategy. Several approaches to scheduling in these environments have been proposed to date. Market driven scheduling as a decentralized solution for such complicated environments has introduced new challenges. In this paper the bidding problem with regard to resources in the reverse auction resource allocation model has been investigated and the new bidding strategies have been proposed and investigated.

• International Journal of Contents
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• 제8권4호
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• Journal of Communications and Networks
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• 제8권3호
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• pp.297-305
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• 2006

High-rate wireless personal area network (HR-WPAN) has been standardized by the IEEE 802.15.3 task group (TG). To support multimedia services, the IEEE 802.15.3 TG adopts a time-slotted medium access control (MAC) protocol controlled by a central device. In the time division multiple access (TDMA)-based wireless packet networks, the packet scheduling algorithm plays a key role in quality of service (QoS) provisioning for multimedia services. In this paper, we propose an adaptive cross-layer packet scheduling method for the TDMA-based HR-WPAN. Physical channel conditions, MAC protocol, link layer status, random traffic arrival, and QoS requirement are taken into consideration by the proposed packet scheduling method. Performance evaluations are carried out through extensive simulations and significant performance enhancements are observed. Furthermore, the performance of the proposed scheme remains stable regardless of the variable system parameters such as the number of devices (DEVs) and delay bound.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1997년도 춘계학술대회 발표논문집
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• pp.235-246
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• 1997

Hybrid fuzzy gain scheduling controller is composed of a PD control and a fuzzy control for taking the advantage of each scheme. The key structure of the hybrid fuzzy gain scheduling control scheme is so called a switch which calculates weighting values between the fuzzy controller and the PD controller. However, due to the requirement of the switch , the hybrid fuzzy gain scheduling control scheme needs extra fuzzy logic processing, thus the structure is complicated. and requires more calculation time. To eliminate the drawbacks, a new hybrid fuzzy gain scheduling control scheme is proposed in this paper. In the proposed scheme, the membership function, for calculating of weithting value, and the input and output membership functions are combined. Thus the proposed hybrid scheme does not require switch for calculation of weighting value, and as a result, the calculation time is faster and the structure is more simple than the existing hybrid controller. Computer simulation results for an inverted pendulum model under Pole-Placement PID controller, fuzzy gain scheduling controller,existing hybrid controller , and proposed hybrid controller are compared to demonstrate the good property of the proposed hybrid controller.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.225-228
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• 2008

In this paper, we presented our implementation of a counter mode AES based on Virtex4 FPGA. Our design exploits three advanced features: composite field arithmetic SubByte, efficient MixColumn transformation, and On-the-Fly Key-Scheduling for fully pipelined architecture. By pipelining the composite field implementation of the S-box, the area cost is reduced to average 17 percent. By designing the On-the-Fly key scheduling, we implemented an efficient key-expander module which is specialized for a pipelined architecture.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• Journal of Computational Design and Engineering
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• 제2권4호
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• pp.206-217
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• 2015

This paper presents a complete S-shape feed rate scheduling approach (CSFA) with confined jerk, acceleration and command feed rate for parametric tool path. For a Non-Uniform Rational B-Spline (NURBS) tool path, the critical points of the tool path where the radius of curvature reaches extreme values are found firstly. Then, the NURBS curve is split into several NURBS sub-curves or blocks by the critical points. A bidirectional scanning strategy with the limitations of chord error, normal/tangential acceleration/jerk and command feed rate is employed to make the feed rate at the junctions between different NURBS blocks continuous. To improve the efficiency of the feed rate scheduling, the NURBS block is classified into three types: short block, medium block and long block. The feed rate profile corresponding to each NURBS block is generated according to the start/end feed rates and the arc length of the block and the limitations of tangential acceleration/jerk. In addition, two compensation strategies are proposed to make the feed rate more continuous and the arc increment more precise. Once the feed rate profile is determined, a second-order Taylor's expansion interpolation method is applied to generate the position commands. Finally, experiments with two free-form NURBS curves are conducted to verify the applicability and accuracy of the proposed method.