• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.147-161
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• 1996

Generally the Multiprocessor Scheduling (MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm (GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and GP/MISF (Critical Path/Most Immediate Successors First). An efficient genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with GA to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.220-229
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• 1995

Generally the Multiprocessor Scheduling(MPS) problem is difficult to solve because of the precedence of the tasks, and it takes a lot of time to obtain its optimal solution. Though Genetic Algorithm(GA) does not guarantee the optimal solution, it is practical and effective to solve the MPS problem in a reasonable time. The algorithm developed in this research consists of a improved GA and CP/MISF(Critical Path/Most Immediate Successors First). A new genetic operator is derived to make GA more efficient. It runs parallel CP/MISF with Ga to complement the faults of GA. The solution by the developed algorithm is compared with that of CP/MISF, and the better is taken as a final solution. As a result of comparative analysis by using numerical examples, although this algorithm does not guarantee the optimal solution, it can obtain an approximate solution that is much closer to the optimal solution than the existing GA's.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.57-68
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• 1995

A general procedure for the numerical solution of coupled, nonlinear, differential two-point boundary-value problems, solutions of which are crucial to the controller design, has been developed and demonstrated. A fixed-end-points, free-terminal-time, optimal-control problem, which is derived from Pontryagin's Maximum Principle, is solved by an extension of Davidenko's method, a differential form of Newton's method, for algebraic root finding. By a discretization process like finite differences, the differential equations are converted to a nonlinear algebraic system. Davidenko's method reconverts this into a pseudo-time-dependent set of implicitly coupled ODEs suitable for solution by modern, high-performance solvers. Another important advantage of Davidenko's method related to the time-optimal problem is that the terminal time can be computed by treating this unkown as an additional variable and sup- plying the Hamiltonian at the terminal time as an additional equation. Davidenko's method uas used to produce optimal trajectories of a single-degree-of-freedom problem. This numerical method provides switching times for open-loop control, minimized terminal time and optimal input torque sequences. This numerical technique could easily be adapted to the multi-point boundary-value problems.

• Structural Engineering and Mechanics
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• v.1 no.1
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• pp.119-135
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• 1993

The paper presents a generalized optimal active control algorithm for earthquake-resistant structures. The study included the weighting matrix configuration, stability, and time-delays for achieving control effectiveness and optimum solution. The sensitivity of various time-delays in the optimal solution is investigated for which the stability regions are determined. A simplified method for reducing the influence of time-delay on dynamic response is proposed. Numerical examples illustrate that the proposed optimal control algorithm is advantageous over others currently in vogue. Its feedback control law is independent of the time increment, and its weighting matrix can be flexibly selected and adjusted at any time during the operation of the control system. The examples also show that the weighting matrix based on pole placement approach is superior to other weighting matrix configurations for its self-adjustable control effectiveness. Using the time-delay correction method can significantly reduce the influence of time-delays on both structural response and required control force.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.572-577
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• 1992

In this paper, the optimal homing guidance problem is investigated for the general missile/target models described in the state-space. The closed-form solution of the optimal guidance law derived, and its asymptotic properties are studied as the time-to-go goes to infinity or zero. Futhermore, several approximate solutions of the optimal guidance law are suggested for real-time applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3689-3700
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• 2016

It is not practically feasible to apply hardware-based fault-tolerant schemes, such as hardware replication, in mobile devices. Therefore, software-based fault-tolerance techniques, such as checkpoint and rollback schemes, are required. In checkpoint and rollback schemes, the optimal checkpoint interval should be applied to obtain the best performance. Most previous studies focused on minimizing the expected execution time or response time for completing a given task. Currently, most mobile applications run in real-time environments. Therefore, it is extremely essential for mobile devices to employ optimal checkpoint intervals as determined by the real-time constraints of tasks. In this study, we tackle the problem of determining the optimal inter-checkpoint interval of checkpoint and rollback schemes to maximize the deadline meet ratio in real-time systems and to build a probabilistic cost model. From this cost model, we can numerically find the optimal checkpoint interval using mathematical tools. The performance of the proposed solution is evaluated using analytical estimates.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.47-53
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• 2016

This paper deals with the capacity constrained time slot assignment problem(CTSAP) that a satellite switches to traffic between $m{\times}n$ ground stations using on-board $k{\leq}_{min}\{m,n\}$ k-transponders switching modes in SS/TDMA time-division technology. There was no polynomial time algorithm to solve the optimal solution thus this problem classified by NP-hard. This paper suggests a heuristic algorithm with O(mn) time complexity to solve the optimal solution for this problem. Firstly, the proposed algorithm selects maximum packet lengths of $\({mn \atop c}\)$ combination and transmits the cut of minimum packet length in each switching mode(MSMC). In the case of last switching mode with inefficient transmission, we applies a compensation strategy to obtain the minimum number of switching modes and the minimum makespan. The proposed algorithm finds optimal solution in polynomial time for all of the experimental data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.310-313
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• 1996

Mathematical programming method for finding optimal solution of job shop scheduling is inadequate to real situation because fo too much computation time. In contrast, dispatching rule is helpful for reducing compuation time but is not guaranted to find optimal solution. The purpose of this paper is to develop a new dispatching rule and procedure to minimize mean flow time whose result is near the optimal solution for job shop scheduling. First step is to select machine which have shortest finishing operation time among the schedulable operations. Second step is to select operation with regard to estimated remaining operation time. The suggested rule is compared with nondelay and MWKR rule for three examples, and is confirmed to be most effective to minimize mean flow time.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.8
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• pp.534-540
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• 2008

In this paper, the optimal bang-bang control problem of an air-conditioning system with slab thermal storage was formulated by gradient method. Furthermore, the numeric solution obtained by gradient method algorithm was compared with the analytic solution obtained on the basis of maximum principle. The control variable is changed uncontinuously at the start time of thermal storage operation in an analytic solution. On the other hand, it is showed as a continuous solution in a numeric solution. The numeric solution reproduces the analytic solution when a tolerance for convergence is applied severely. It is conceivable that gradient method is effective in the analysis of the optimal bang-bang control of the large-scale system like an air-conditioning system with slab thermal storage.