• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.635-642
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• 1989

We formulated the multi-robot trajectory problem into a series of NLP problem, each of which is that of finding the optimal tip positions of the robots for the next time step. The NLP problem is composed of an objective function and three constraints, namely: a) Joint position limits, b) Joint velocity limits, and c) Collision-avoidance constraints. By solving a series of NLP problem, optimally coordinated trajectories can be determined without requiring any prior path information. This is a novel departure from the previous approach in which either all paths or at least one path is assumed to be given. Practical application of the developed method is for optimal synthesis of multiple robot trajectories in off-line. To test the validity and effectiveness of the method, numerical examples are illustrated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1779-1786
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• 2002

When the topology optimization is applied to the design of compliant mechanism, unexpected displacements of input and output port are generated since the displacement control is not included in the formulation. To devise a more precise mechanism, displacement constraint is formulated using the mutual potential energy concept and added to multi-objective function defined with flexibility and stiffness of a structure. The optimization problem is resolved by using Finite Element Method(FEM) and Sequential Linear Programming(SLP). Design examples of compliant mechanism with displacement constraint are presented to validate the proposed design method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.8-13
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• 2003

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives In a stationary Poisson process The problem Is formulated using METRIC-approximation in a combined approach of pricing and (S-1.S) Inventory policy, for which an iterative solution algorithm is derived with respect to the corresponding one-warehouse multi-retailor supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed The computational results show that the proposed algorithm is efficient and derives quite good decisions

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.2
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• pp.8-15
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• 2008

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.35-42
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• 2008

Most of tasks for vertical surface work in shipyard have been accomplished by human workers. However, such manual work often causes injury to workers, also the production cost becomes high due to increasing individual wage. To cope with the circumstance, shipbuilding companies try to introduce wall-climbing robots for carrying out such kind of tasks. In designing a wall-climbing robot, it is essential to minimize its own weight to improve the performance such as moving speed and power saving. For such purpose. this study proposes a method of optimal design for a wall-climbing robot using a genetic algorithm with multi-objective function. Specifically, the thickness of the robot base is minimized to reduce the weight while maintaining the allowable strength and avoiding the resonance frequencies. The proposed method is applied to the design of a wall-climbing robot, and the result shows that the method is useful at an early design stage.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.61-66
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• 1992

In this paper, a method for implementing software for the control system with dual structure in processor module is proposed and implemented to enhance its reliability. In this implementation the multi-tasking function which is provided by a real-time operating system is applied. The overall softwre is divided into five tasks and is performed in each of the dual processor module, independently. By this, the processor module with dual structure can achieve a control objective and fault diagnostics effectively. An experimental result shows that the backup processor module can be substituted for the primary processor module immediately when it happens to fail, because data relating the failure information are exchanged continuously done via shared memories.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1763-1768
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• 2003

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.82-84
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• 2006

최근의 생물학적인 연구에 DNA microarray가 널리 쓰이고 있기 때문에, 이러한 DNA microarray를 구성하는데 필요한 probe design 작업의 중요성이 점차 커져가고 있다. 이 논문에서는 probe design 문제를 thermodynamic fitness function이 2개인 multi-objective optimization 작업으로 변환한 뒤, ${\epsilon}$-multiobjective evolutionary algorithm을 이용하여 probe set을 찾는다. 또한, probe 탐색공간의 크기를 줄이기 위하여 각 DNA sequence의 primer 영역을 찾는 작업을 진행하며, 사용자가 직접 프로그램을 테스트할 수 있는 웹사이트를 제공한다. 실험 대상으로는 mycoides를 선택하였으며, 이 논문에서 제안된 방법을 사용하여 성공적으로 probe set을 발견할 수 있었다.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.291-293
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• 1999

This paper proposed the optimal operational scheduling of cogeneration system for paper mill connected with several auxiliary devices. Auxiliary devices that include auxiliary boilers, waste heat boilers and sludge incinerators operate with multi-cogeneration systems. Especially environment element was considered in objective function to solve the environment problem. And GAs(Genetic Algorithms) was applied to optimize and to analyse nonlinear operational property of cogeneration system of paper mill connected with several auxiliary devices. C-language was used to GAs computation. Electricity can be purchased through power system from utility. The proposed operational strategy on cogeneration system for paper mill to increase energy efficiency can be applied to the similar cogeneration system of industrial field.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1088-1090
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• 1997

This paper presents an effective methodology of optimal environmental and economic operation using evolution strategy. In power systems, evolution strategy, based on natural selection and genetics, can analyze non-linear and discontinuous functions in global search techniques. The formulation using this search techniques is multi-objective function, which consists of fuel cost and environmental effects concerning the pollution of the Earth's atmosphere caused by the emission of $SO_2$ and $NO_x$ from thermal generator plants. The proposed algorithms are applied on system with 6 generator.