• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.161-167
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• 2008

In this paper, the optimal design of trusses using advanced analysis and genetic algorithm is performed. An advanced analysis takes into account geometric nonlinearity and material nonlinearity. The micro genetic algorithm is used as optimization technique. The weight of structures is treated as the objective function. The constraint functions are defined by load-carrying capacities and displacement requirement. The effectiveness of the proposed method is verified by comparing the results of the proposed method with those of other method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3060-3062
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits (CNC) is proposed. The proposed algorithm compute the optimal path using subgoal-based dynamic programming algorithm. In the algorithm, the optimal paths are computed regardless of the distance between the initial and the goal position. It begins to find subgoals starting from the initial position when the output of the initial cell becomes nonzero value. The suboal is set as the initial position to find the next subgoal until the final goal is reached. Simulations have been done considering the imprecise hardware fabrication and the limitation of the magnitude of input value.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.590-597
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• 2009

The final quality of the workpiece is affected by the grinding process that has been conducted in final manufacturing stage. However the quality-satisfaction of ground workpiece depends on the skill of an expert in this process. Therefore, the process models of grinding have been developed to predict the states according to grinding process. In this paper, in order to find the optimized grinding condition to reduce the manufacturing expense and to meet requirements of ground workpiece optimization algorithm using E.S.(Evolutionary Strategy) is proposed. The proposed algorithm has been employed to find the optimal grinding and dressing condition using the grinding process models and nonlinear grinding constraints. The optimized results also presents the guide line of grinding process. The effectiveness of the proposed algorithm is verified through the experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.215-220
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• 1998

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1389-1391
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• 1996

In this paper, we applies two methods - Genetic Algorithm(GA) and $A^*$ Algorithm - to find the optimal path in route guidance system. Under the assumption that the traveling costs of each link are given, the task to find the optimal path becomes very complicated problem if the number of nodes or links increase. Two well-known algorithms are modified to resolve the problem and the preliminary demonstration show both optimistic result and needs to improvement.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.217-224
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• 1986

In case of VLSI design, the shuffle-exchange graph is useful for optimal layout. HOEY and LEISERSON proposed the method of drawing a N-nodes shuffle-exchange graph on O(N2/log N) layout area by using the complex plane digram. [2] In this paper, a new algorithm for drawing the shuffle-exchange graph is proposed. This algorithm is not by using the complex plane diabram, but the table of e decimal represented nodes of shuffle-edge relations. And the structural properties for optimal layout of the graph are summarized and verified. By using this more simplified algorithm, a FORTRAN program which can be treated faster is written. Aimed near optimal shuffle-exchange graphs are printed out by giving inputs` the number of nodes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1079-1088
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• 2004

Generally, the code motion algorithm accomplishes the run-time optimal connected with the computational optimifation and the register overhead This paper proposes a sparse code motion, which considers the code size, in addition to computational optimization and lifetime optimization. The BCM algorithm carries out the optimal code motion computationally and the LCM algorithm reduces the register overhead in a sparse code motion algorithm. A sparse code motion algorithm is optimum algorithm computationally and lifetime because of suppression unnecessary code motion This algorithm improves runtime and efficiency of the program than the previous work through the performance test.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1169-1182
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• 2020

The ant colony optimization (ACO) algorithm is a classical metaheuristic optimization algorithm. However, the conventional ACO was liable to trap in the local minimum and has an inherent slow rate of convergence. In this work, we propose a novel combinatorial ACO algorithm (CG-ACO) to alleviate these limitations. The genetic algorithm and the cloud model were embedded into the ACO to find better initial solutions and the optimal parameters. In the experiment section, we compared CG-ACO with the state-of-the-art methods and discussed the parameter stability of CG-ACO. The experiment results showed that the CG-ACO achieved better performance than ACO_R, simple genetic algorithm (SGA), CQPSO and CAFSA and was more likely to reach the global optimal solution.

• The Journal of Information Systems
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• v.17 no.3
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• pp.39-58
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• 2008

Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.