• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1145-1149
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• 1990

This paper proposes a numerical method for redundant manipulators using predetermined optimal resolution. In order to obtain optimal joint trajectories, it is desirable to formulate redundancy resolution as an optimization problem having an integral cost criterion. We predetermine the trajectories of redundant joints in terms of the Nth partial sum of the Fourier series, which lead to the solution in the desirable homotopy class. Then optimal coefficients of the Fourier series, which yield the optimal solution within the predetermined class, are searched by the Powell's method. The proposed method is applied to a 3-link planar manipulator for cyclic tasks in Cartesian space. As the results, we can obtain the optimal solution in the desirable homotopy class without topological liftings of the solution. To show the validity of the proposed method, we analyze both optimal and extremal solutions by the Fast Fourier Transform (FFT) and discuss joint trajectories on the phase plane.

• Journal of Ship and Ocean Technology
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• 제5권1호
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• pp.30-37
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• 2001

Ship optimal design is a multi-objective decision-making process and its optimal solution does not exit in general. It is a problem in which the decision-maker is very interested that an effective solution is how to be found which has good characteristic and is substituted for optimal solution in a sense. In the previous methods of multi-objective decision-making, the weighting coefficients are decided from the point of view of individuals which have a bit sub-jective an unilateral behavior. in order to fairly and objectively decide the weighting coeffi-cients, which are considered to be optimal in all system of multi-objective decision-making and satisfactory solution to the decision-maker, the pater presents a method of applying the Technology of the Biggest Entropy. It is proved that the method described in the paper is very feasible and effective be means of a practical example of ship optimal design.

• 한국경영과학회지
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• 제21권1호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1995년도 추계학술대회발표논문집; 서울대학교, 서울; 30 Sep. 1995
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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.

• 에너지공학
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• 제13권2호
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• pp.128-132
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• 2004

본 연구에서는 급전계획의 파레토최적해를 구하는 새로운 방법을 제시하였다. 이를 위하여, 고찰기간에 대해 총 오염물질배출량을 고려하여 최적경제부하배분을 할 수 있는 동적계획법을 도입하였으며, 최적급전계획의 결과를 군으로 얻을 수 있는 파레토최적해를 얻는 방법을 개발하였다. 이 결과, 의사결정자는 파레토최적해를 얻을 수 있으며, 이중에서 하나의 해를 선택하여 사용할 수 있게 되었다. 제안한 방법을 시험계통에 적용하여 유용성을 검증하였다.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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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.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.131-138
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• 2016

In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

• Journal of applied mathematics & informatics
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• 제42권3호
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• pp.647-661
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• 2024

This study aims to determine the optimal solution to transportation problems. We proposed a novel approach for tackling the initial basic feasible solution. This is a critical step toward achieving an optimal or near-optimal solution. The transportation issue is an issue of distributing goods from several sources to several destinations. The literature demonstrates many ways to improve IBFS. In this work, to solve the IBFS, we suggested a new method based on the statistical formula called cumulative distribution function (CDF) in exponential distribution, and inverse contra-harmonic mean (ICHM). The spreadsheet converts transportation cost values into exponential cost cell values. The stepping-stone method is used to identify an optimum solution. The results are compared with other existing methodologies, the suggested method incorporates balanced, and unbalanced, maximizing the profits, random values, and case studies which produce more effective outcomes.

• 대한산업공학회지
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• 제28권1호
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• pp.99-104
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• 2002

This paper presents a method of sensitivity analysis for the infeasible interior point method when a new variable is introduced. For the sensitivity analysis in introducing a new variable, we present a method to find an optimal solution to the modified problem. If dual feasibility is satisfied, the optimal solution to the modified problem is the same as that of the original problem. If dual feasibility is not satisfied, we first check whether the optimal solution to the modified problem can be easily obtained by moving only dual solution to the original problem. If it is possible, the optimal solution to the modified problem is obtained by simple modification of the optimal solution to the original problem. Otherwise, a method to set an initial solution for the infeasible interior point method is presented to reduce the number of iterations required. The experimental results are presented to demonstrate that the proposed method works better.

• East Asian mathematical journal
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• 제38권1호
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• pp.21-31
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• 2022

This paper is concerned with the optimal control problem associated to the self-organizing target detection model in 1D domains. That is, we show the global existence of weak solution and the existence of optimal control.