• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.297-300
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• 1997

This paper uses genetic algorithm (GA) for optimal control. GA can find optimal control profile, but the profile may be oscillating feature. To make profile smooth, fuzzy genetic algorithm (FGA) is proposed. GA with fuzzy logic techniques for optimal control can make optimal control profile smooth. We describe the Fuzzy Genetic Algorithm that uses a fuzzy knowledge based system to control GA search. Result from the simulation example shows that GA can find optimal control profile and FGA makes a performance improvement over a simple GA.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.139-147
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• 2012

This paper suggests simple search algorithm for optimal solution in assignment problem. Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm. The proposed algorithm reduces the 4 steps of Hungarian algorithm to 1 step, and only selects the minimum cost of row and column then gets the optimal solution simply. For the 27 balanced and 7 unbalanced assignment problems, this algorithm finds the optimal solution but the genetic algorithm fails to find this values. This algorithm improves the time complexity O($n^3$) of Hungarian algorithm to O(n). Therefore, the proposed algorithm can be general algorithm for assignment problem replace Hungarian algorithm.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.955-960
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• 2009

In order to improve the efficiency of the main transformer in a tilting train, the optimal operation of a cooling system is necessary. Mathematical models of a main transformer cooling system were developed. These include models for the main transformer, the oil pump, the oil cooler, and the blower. The optimal oil temperature algorithm was also developed. This consists of the optimal setpoint algorithm and the control algorithm. A simulation program was developed by using mathematical models and the optimal oil temperature algorithm. Simulation results showed that the dynamic behavior of a main transformer cooling system was predicted well by mathematical models and a main transformer cooling system was controlled effectively by the optimal oil temperature algorithm.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.149-152
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• 2002

The aim of this study is to analyse the problems occurred by using classical algorithm to synthesize the H$\infty$ optimal controller. The obtained result of analysis applied to the composition of algorithm for the new H$\infty$ optimal controller which was introduced in this study. The study investigates and compares H$\infty$ optimal controller formed by new algorithm with the one formed by classical algorithm. In particular, robustness related to the robust control is systematically described by using the composition of algorithm for the classical H$\infty$ optimal controller. In addition, the flow charts classified into classical algorithm and new one are discussed to synthesize the H$\infty$ optimal controller.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1271-1282
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• 2022

The optimal design of Water Distribution System (WDS) is used in various ways according to the purpose set by the user. The optimal design of WDS has various purposes, such as minimizing costs and minimizing energy generated when manufacturing pipes. In this study, based on the Modified Hybrid Vision Correction Algorithm (MHVCA), a cost-optimal design was conducted for various WDSs. We also propose a new evaluation index, Best Rate (BR). BR is an evaluation index developed based on the K-mean Clustering Algorithm. Through BR, a comparison was made on the possibility of searching for the optimal design of each algorithm used in the optimal design of WDS. The results of MHVCA for WDS were compared with Vision Correction Algorithm (VCA) and Hybrid Vision Correction Algorithm (HVCA). MHVCA showed a lower cost design than VCA and HVCA. In addition, MHVCA showed better probability of lower cost designs than VCA and HVCA. MHVCA will be able to show good results when applied to the optimal design of WDS for various purposes as well as the optimal design of WDS for cost minimization applied in this study.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.786-792
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• 2011

The present paper presents an optimal capacitor placement (OCP) algorithm for voltagestability enhancement. The OCP issue is represented using a mixed-integer problem and a highly nonlinear problem. The hybrid particle swarm optimization (HPSO) algorithm is proposed to solve the OCP problem. The HPSO algorithm combines the optimal power flow (OPF) with the primal-dual interior-point method (PDIPM) and ordinary PSO. It takes advantage of the global search ability of PSO and the very fast simulation running time of the OPF algorithm with PDIPM. In addition, OPF gives intelligence to PSO through the information provided by the dual variable of the OPF. Numerical results illustrate that the HPSO algorithm can improve the accuracy and reduce the simulation running time. Test results evaluated with the three-bus, New England 39-bus, and Korea Electric Power Corporation systems show the applicability of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.465-472
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• 2004

Analog CPPN-based optimal road boundary detection algorithm for autonomous vehicle is proposed. The CPPN is a massively connected analog parallel array processor. In the paper, the dynamic programming which is an efficient algorithm to find the optimal path is implemented with the CPPN algorithm. If the image of road-boundary information is utilized as an inter-cell distance, and goals and start lines are positioned at the top and the bottom of the image, respectively, the optimal path finding algorithm can be exploited for optimal road boundary detection. By virtue of the parallel and analog processing of the CPPN and the optimal solution of the dynamic programming, the proposed road boundary detection algorithm is expected to have very high speed and robust processing if it is implemented into circuits. The proposed road boundary algorithm is described and simulation results are reported.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.89-96
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• 1991

When a feasible solution approaches to the optimal extreme point in Karmakar's algorithm, components of the search direction vector for a solution converge at a certain value according to the corresponding columns of the optimal basis and the optimal nonbasis. By using this convergence properties of Karmarkar's algorithm, we can identify columns of the optimal basis before the final stage of the algorithm. The complexity of Karmarker's algorithm with newly proposed termination criterion does not increase. A numerical experiments for the problems which were generated by random numbers are also illustrated. Experimental results show that the number of iterations required for determining columns of the optimal basis depends on problems. For all cases, however, columns of the optimal basis are exactly verified when this termination criterion is used.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.13-22
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• 1993

The aircraft scheduling, which is used to determine flight frequency, departure times and aircraft type assignments, is main problem of airline's planning. This paper proposes a new algorithm for aircraft scheduling that is to maximize airline profits. This paper proposes a column generation algorithm to get an optimal solution of the continous relaxation not using all the feasible variables, but using only a limited number of variables that is generated whenever it is necessary. Using this algorithm, proposes an optimal algorithm to get an optimal integer solution of aircraft scheduling problem efficiently. The effectiveness of the column generation algorithm and the optimal algorithm is illustrated by the computational results obtained from a series of real airline problems.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.