• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1796-1801
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• 2001

For micro-machines, very few design methodologies based on optimization hale been developed so far. To overcome the difficulties of design optimization of micro-machines, the search method for multi-dimensional design window (DW)s is proposed. The proposed method is defined as areas of satisfactory design solutions in a design parameter space, using both continuous evolutionary algorithms (CEA) and the modified K-means clustering algorithm . To demonstrate practical performance of the proposed method, it was applied to an optimal shape design of micro electrostatic actuator of optical memory. The shape design problem has 5 design parameters and 5 objective functions, and finally shows 4 specific design shapes and design characters based on the proposed DWs.

• Proceedings of the KIPE Conference
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• 2004.11a
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• pp.14-17
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• 2004

In this paper, an optimal design method to have a good performance is researched. The parameters which are senstive to the performance are examined and determined by using evolutionary computations and commercial CAD program to have good performance. Design method simulated is compared with conventional procedure.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.2
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• pp.224-229
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• 2010

This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic topology optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. RBTO based on BESO starting from various design domains produces a similar optimal topology each other. Numerical examples are presented to compare the DTO with the RBTO.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.297-300
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• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.2
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• pp.127-135
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• 2002

Due to the fact that the design of a reinforced concrete structure changes in accordance with its shape and assigned load, total automation of the design system has not been achieved. For instance, since there is no general rule about setting up reinforcing steel quantity and arrangement location, it is simply not feasible to automatically decide the reinforcing arrangement location. In this study, the ESO(evolutionary structural optimization) technique and its related issues will be discussed. The ESO techniques is determined the reasonable load path which is traveling of load between in-flow and out-flow at a concrete structure using numerical analysis. And the results applied to the steel arrangement in reinforced concrete structures. The optimal algorithm, which determines the terminal criteria during ESO process, has been updated by using the obtained results. And the load path within the member has been determined automatically.

• Structural Engineering and Mechanics
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• v.51 no.5
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• pp.707-725
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• 2014

In order to improve the crane-hook's performance and service life, we formulate a multi-criteria shape design problem considering practical conditions. The structural weight, the displacement at specified points and the induced matrix norm of stiffness matrix are adopted as the evaluation items to be minimized. The heights and widths of cross-section are chosen as the design variables. The design variables are expressed in terms of shape functions based on the Gaussian function. For this multi-objective optimization problem with three items, we utilize a multi-objective evolutionary algorithm, that is, the multi-objective Particle Swarm Optimization (MOPSO). As a common feature of obtained solutions, the side views are tapered shapes similar to those of actual crane-hook designs. The evaluation item values of the obtained designs demonstrate importance of the present optimization as well as the feasibility of the proposed optimal design approach.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.7
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• pp.369-373
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• 2006

In this paper, an optimal method for determining design parameters of a Switched Reluctance Motor is researched. The dominant design parameters are stator and rotor pole arc and switching on and off angle. The parameters affecting performance are examined and selected using evolutionary computations and commercial CAD program. The simulated design method is compared with conventional procedure.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.247-257
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• 2005

Generally, the network topology design problem is characterized as a kind of NP-hard combinatorial optimization problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size. In this paper, we propose the efficient approach with two phase that is comprised of evolutionary computation approach based on Prufer number(PN), which can efficiently represent the spanning tree, and a heuristic method considering 2-connectivity, to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability: firstly, to find the spanning tree, genetic algorithm that is the most widely known type of evolutionary computation approach, is used; secondly, a heuristic method is employed, in order to search the optimal network topology based on the spanning tree obtained in the first Phase, considering 2-connectivity. Lastly, the performance of our approach is provided from the results of numerical examples.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.186-195
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• 2005

This paper deals with attitude control design for a thruster system which is mainly used as a control system of space vehicles. Attitude controllers are designed based on a simple blowing-down thruster system structure. In order to consider severe time-delay effects of the thruster system during controller design, the control design problem is defined based on the corresponding limit cycle analysis. Optimal roll controllers and optimal pitch/yaw controllers are resulted from co-evolutionary optimum design processes for each flight phase. The control performances are verified by computer simulations.