• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.1
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• pp.71-78
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• 2005

Rescaled Simulated Annealing(RSA) has been devised for improving the disadvantage of Simulated Annealing(SA) which requires tremendous amount of computation time. RSA and SA have been for optimization of truss and satellite structures and for comparison of results from two algorithms. Ten bar truss structure which has continuous design variables are optimized.. As a practical application, a satellite structure is optimized by the two algorithms. Weights of satellite upper platform and propulsion module are minimized. MSC/NASTRAN is used for the static and dynamic analysis. The optimization results of the RSA are compared with results of the classical SA. The numbers of optimization iterations could be effectively reduced by the RSA.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.570-575
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• 2004

This paper deals with the exchange of tourists and the operation of sightseeing train encouraged by the inter-Korean cross-border railway project. First of all, how the inter-Korean cross-border railway project has developed will be discussed. After this, the present tourism state, facilities, the state of railways and roads of North Korea, and major tourist attraction around the Kyonguisun will be shown. And then, several aspects on the agreements between the Korean National Railroad (KORAIL) and North Korean railroad system will be summarized. And, finally, the economic effect of the line including the operation schedule of the Kyonguisun sightseeing train, the demand forecast, the computation of railway fare, and profit sharing will be depicted.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.6 s.336
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• pp.49-58
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• 2005

In this paper, we propose an optimal ILP scheduling algorithm for multiprocessor design on LDFG(Linear Data-Flow Graph) that can be represented by homogeneous synchronous data-flow. The proposed computation in this paper does not contain data-dependent, all scheduling decisions for such algorithms can be taken at compile time, only fully static overlapped schedules are considered. It means that all linear have the same schedule and the same processor assignment. In this paper, the resource-constrained problem is addressed, for the LDFG optimization for multiprocessor design problem formulating ILP solution available to provide optimal solution. The results show that the scheduling method is able to find good quality schedules in reasonable time.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1215-1219
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• 2006

Scheduling plays an important role in the process management in terms of providing profit-maximizing operation sequence of multiple orders and estimating completion times of them. In order to takes its full potential, varying conditions should be properly reflected in computing the schedule. The adjustment of scheduling decisions has to be made frequently in response to the occurrence of variations. It is often challenging because their model has to be adjusted and their solutions have to be computed within short time period. This paper employs Model Predictive Control(MPC) principles for updating the process condition in the scheduling model. The solutions of the resulting problems considering variations are computed using parametric programming techniques. The key advantage of the proposed framework is that repetition of solving similar programming problems with decreasing dimensionis avoided and all potential schedules are obtained before the execution of the actual processes. Therefore, the proposed framework contributes to constructing a robust decision-support tool in the face of varying environment. An example is solved to illustrate the potential of the proposed framework with remarks on potential wide applications.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.69-76
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• 2010

This paper proposed a new fast multi-reference frame motion estimation algorithm. The proposed algorithm reduces search areas of motion estimation using a linear relation of motion vector with distance of each reference frame. New algorithm executes full search area motion estimation in reference frame 0 and reference frame 1. After that, search areas in reference frame 2, reference frame 3 and reference frame 4 are minimized by distance of each reference frame and results of motion estimation in reference frame 0 and reference frame 1. The proposed algorithm does not use a threshold value which is obstacle of hardware implementation and processing time schedule. Also, it reduced computation quantity of multi-reference motion estimation. Hardware implementation of multi-reference frame motion estimation is possible by these features. Simulation results show that PSNR drop and bitrate increase of proposed algorithm are lower than those of previous fast multi-reference frame motion estimation algorithm The number of computation of new algorithm is reduced 52.5% and quality of result is negligible when compared with full search area motion estimation which has 5 reference frames.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.8
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• pp.619-630
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• 2003

We present a method of runtime configuration scheduling in reconfigurable SoC design. As a model of computation, we use a popular formal model of computation, hierarchical FSM (HFSM) with synchronous dataflow (SDF) model, in short, HFSM-SDF model. In reconfigurable SoC design with HFSM-SDF model, the problem of configuration scheduling becomes challenging due to the dynamic behavior of the system such as concurrent execution of state transitions (by AND relation), complex control flow (HFSM), and complex schedules of SDF actor firing. This makes it hard to hide configuration latency efficiently with compile-time static configuration scheduling. To resolve the problem, it is necessary to know the exact order of required configurations during runtime and to perform runtime configuration scheduling. To obtain the exact order of configurations, we exploit the inherent property of HFSM-SDF that the execution order of SDF actors can be determined before executing the state transition of top FSM. After obtaining the order information and storing it in the ready configuration queue (ready CQ), we execute the state transition. During the execution, whenever there is FPGA resource available, a new configuration is selected from the ready CQ and fetched by the runtime configuration scheduler. We applied the method to an MPEG4 decoder and IS95 design and obtained up to 21.8% improvement in system runtime with a negligible overhead of memory usage.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.491-496
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• 2002

Most partitioning algorithms for hardware- software codesign do not consider scheduling. Therefore, partitioning should be performed again if time constraints art not satisfied in scheduling the partitioned results. Existing FDS-applied methods which consider scheduling in partitioning decide the control step of the node to schedule while selecting nodes for partitioning. In selecting nodes for partitioning, several aspects should be considered together such as added cost or time due to the partition of the node, or the degree of interference due to the scheduling of the node. At this time, the induced force, which means the degree of intereference of scheduling other nodes, is computed all over the control step of the corresponding node and other depending nodes. In this paper, a new FDS-applied partitioning algorithm is proposed, where partitioning is performed using the defined scheduling urgency and relative scheduling urgency of the nodes. Since the nodes are partitioned by the computation of relative scheduling urgencies only at the earliest control step and the latest control step among the assignable steps, the time complexity for the computation of induced force could be improve. Experimental result on the benchmarks show the improvement of execution time of the proposed algorithm compared to the existing FDS-applied methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.89-97
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• 2016

This paper addresses the problem of the construction planning of artillery positions, for which we present an optimization model and propose a heuristic algorithm to solve problems of practical size. The artillery position construction plan includes the assignment of engineers to support the artillery and the schedule of the support team construction sequence. Currently, in the army, managers construct the plan based on their experience. We formulate the problem as a mixed integer program and present a heuristic that utilizes the decomposition of the mixed integer model. We tested the efficacy of the proposed algorithm by conducting computational experiments on both small-size test problems and large-size practical problems. The average optimality gap in the small-size test problem was 6.44% in our experiments. Also, the average computation time to solve the large-size practical problems consisting of more than 200 artillery positions was 79.8 seconds on a personal computer. The result of our computational experiments shows that the proposed approach is a viable option to consider for practical use.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1678-1685
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• 1999

In most of the existing real-time schedulers producing the total value as large as possible, the service times for all schedulable tasks are computed at each time a new task arrives. If all scheduled tasks would be executed completely before a new task arrives, the schedule may produce the greatest total value. But this is not always true in real situations. In many cases, (a) new tasks arrive(s) before all the scheduled tasks are executed completely. In this paper, we propose a unique scheduling algorithm for real-time tasks. The proposed algorithm determines the service times only for some tasks with earlier deadlines while the existing algorithms determine the service times for all tasks. This partial computation decreases the average scheduling complexity ramatically, even though, in the worst case, the complexity of the proposed algorithm becomes O(N2), which is equal to that of a previous algorithm that has been known as a less complicated one.