• 디지털융복합연구
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• 제15권3호
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• pp.181-186
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• 2017

시스템 최적화는 소스코드의 변경 없이 중복된 모듈을 추출하고, 추출된 모듈의 재사용을 위하여 프로그램의 구조를 변경하는 기법이다. 구조지향 개발과 객체지향 개발은 크로스커팅 영역의 모듈화에는 효율적이나 크로스커팅 개념을 모듈화 할 수 없다. 기존 시스템에서 크로스커팅 개념을 적용하기 위해, 각 시스템 내에 분산되어 있는 시스템 최적화 대상 모듈을 크로스커팅 영역으로 추출하는 기술이 필요하다. 본 논문에서는 개발이 완료된 시스템에서 중복 모듈을 추출하기 위한 방법을 제안한다. 제안하는 방법은 소스코드 분석을 통해 데이터 의존관계와 제어 의존관계를 분석하여 중복되는 요소를 추출한다. 추출된 중복된 요소는 시스템 최적화를 위하여 프로그램 의존 관계 분석에 사용될 수 있다. 중복된 의존관계 분석 결과는 제어 흐름 그래프로 변환되며, 이를 활용하여 최소 크로스커팅 모듈을 생성할 수 있다. 의존 관계 분석을 통해 추출된 요소는 크로스커팅 영역 모듈로 설정함으로써 시스템 내 중복된 코드를 최소화 할 수 있는 시스템 최적화 방법을 제시한다.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1143-1155
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• 2001

In order to reduce the expensive CPU time for design sensitivity analysis in dynamic response optimization, this study introduces the design sensitivities approximated within estimated confidence radius in dynamic response optimization with ALM method. The confidence radius is estimated by the linear approximation with Hessian of quasi-Newton formula and qualifies the approximate gradient to be validly used during optimization process. In this study, if the design changes between consecutive iterations are within the estimated confidence radius, then the approximate gradients are accepted. Otherwise, the exact gradients are used such as analytical or finite differenced gradients. This hybrid design sensitivity analysis method is embedded in an in-house ALM based dynamic response optimizer, which solves three typical dynamic response optimization problems and one practical design problem for a tracked vehicle suspension system. The optimization results are compared with those of the conventional method that uses only exact gradients throughout optimization process. These comparisons show that the hybrid method is more efficient than the conventional method. Especially, in the tracked vehicle suspension system design, the proposed method yields 14 percent reduction of the total CPU time and the number of analyses than the conventional method, while giving similar optimum values.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1994년도 추계학술발표회 및 정기총회
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.

• 한국시뮬레이션학회논문지
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• 제12권2호
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• pp.1-11
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• 2003

In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• Journal of Biosystems Engineering
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• 제29권1호
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• pp.53-58
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• 2004

The purpose of this study was to evaluate an optimization model to determine the operation conditions of the chestnuts flame peeling system. The results of this study were summarized as follows. The optimization model was developed and evaluated to represent the flame peeling characteristics of the domestic chestnuts. When the heating depth was selected for various utilization of the peeled chestnuts, the model could determine the optimal conditions of the hardness of the chestnut shells, the flame temperature, and the flame time to get the maximum peeling ratio of the chestnut flame peeling system. When the heating depth was limited to 2.2 mm, the optimization model determined the proper operation conditions and the maximum peeling ratio such as 1594 g/$\textrm{mm}^2$ of the hardness of the chestnut shells, 780$^{\circ}C$ of the flame temperature, 29 second of the flame time, and 98.1 % of the peeling ratio.

• Structural Engineering and Mechanics
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• 제88권3호
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• pp.273-285
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• 2023

This study examines how the interaction between soil and a wind turbine's supporting system affects the optimal design. The supporting system resting on an elastic soil foundation consists of a steel conical tower and a concrete circular raft foundation, and it is subjected to wind loads. The material cost of the supporting system is aimed to be minimized employing various metaheuristic optimization algorithms including teaching-learning based optimization (TLBO). To include the influence of the soil in the optimization process, modified Vlasov and Gazetas elastic soil models are integrated into the optimization algorithms using the application programing interface (API) feature of the structural analysis program providing two-way data flow. As far as the optimal designs are considered, the best minimum cost design is achieved for the TLBO algorithm, and the modified Vlasov model makes the design economical compared with the simple Gazetas and infinitely rigid soil models. Especially, the optimum design dimensions of the raft foundation extremely reduce when the Vlasov realistic soil reactions are included in the optimum analysis. Additionally, as the designated design wind speed is decreased, the beneficial impact of soil interaction on the optimum material cost diminishes.

• Advances in aircraft and spacecraft science
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• 제4권6호
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• pp.701-709
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• 2017

One of the components that used in the satellite thermal control subsystem is the Mechanically Pumped Fluid Loop (MPFL) system; this system mostly used in geosynchronous orbit (GEO) satellites, and can transfer heat from a hot point to a cold point using the fluid which circulated in a closed loop. Heat radiates to the deep space at the cold plate to cool down the fluid temperature. In this research, the radiative heatexchanger (RHX) for a MPFL system is optimized. The genetic algorithm has been used for minimizing the total mass and pressure drop by considering a constant transferred heat rate at the heat exchanger. The optimization has been done in two cases. In case I, two parameters are considered as a goal function, so optimization is performed using NSGA-II method. Results of optimization are shown in the pareto diagram. In case II, the diameter of pipe is considered constant, so the optimized value for distances of the parallel pipes is obtained by using the genetic algorithm, in which the system has the least total mass. Results show that in the RHX, by increasing the pipe diameter, pressure drop decreases and total mass increases. Also by considering a constant value for pipe diameter, an optimum distance between pipes and pipe length are obtained in which the system has a minimum mass.

• 한국항공우주학회지
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• 제35권12호
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• pp.1121-1128
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• 2007

다분야 통합 최적설계(MDO)는 여러 설계분야가 복잡하게 얽혀서 설계가 진행되어야 하는 항공기나 우주발사체등의 설계에 매우 유용하게 적용되고 MDO 시스템은 다양한 설계 분야의 통합적이고 동시적인 해석 및 설계 최적화를 위한 통합 환경 또는 시스템이다. MDO 시스템은 이기종의 환경에서 분산되어있는 다양한 해석 코드 및 최적화 코드, CAD, DBMS, GUI등의 자원들을 통합하고 효율적으로 사용할 수 있어야하며 협업설계환경을 제공해야한다. 본 논문에서는 웹 서비스 기반의 글로버스 툴킷을 이용해 설계자원들을 통합하고 워크플로우, 에이전트 등의 자동화 기술을 이용해 유기적인 자동실행을 제공하며 웹 유저 인터페이스를 통해 협업설계환경을 제공하는 웹 서비스 기반 MDO 시스템의 구축방안을 제시한다.

• Smart Structures and Systems
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• 제32권6호
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• pp.383-391
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• 2023

Energy harvesting in trams may become a prevalent source of passive energy generation due to the high density of vibrational energy, and this may help power structural health monitoring systems for the trams. This paper presents a broadband vibrational energy harvesting device design that utilizes a varied frequency from a tram vehicle using a 2 DOF vibrational system combined with electromagnetic energy conversion. This paper will demonstrate stepwise optimization processes to determine mechanical parameters for frequency tuning to adjust to the trams' operational conditions, and electromagnetic parameters for the whole system design to maximize power output. The initial optimization will determine 5 important design parameters in a 2 DOF vibrational system, namely the masses (m₁, m₂ (and spring constants (k₁, k₂, k₃). The second step will use these parameters as initial guesses for the second optimization which will maintain the ratios of these parameters and present electrical parameters to maximize the power output from this system. The obtained values indicated a successful demonstration of design optimization as the average power generated increased from 1.475 mW to 17.44 mW (around 12 times).

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2008년도 춘계학술대회
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• pp.620-627
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• 2008

In this paper, recognizing the importance of the database query optimization design methods, we implemented mobile database with mobile program (J2ME) which is a useful database procedures. In doing so, we emphasize the logical query optimization which brings mobile database to performance improvement. The research implies that the suggested mobile program (J2ME) would contribute to the realization of the efficient mobile database as the related technology develops in the future.