• 물과 미래
• /
• 제26권2호
• /
• pp.89-97
• /
• 1993

Monte Carlo 기법을 이용하여 저수지군으로부터 위험도나 신뢰도를 고려한 시스템 편익을 최적화하기 위해서는 수많은 모의발생 유입량 자료군을 이용하여야 한다. 본 연구에서는 저수지군 연계운영을 위한 모의 발생 유입량 자료를 시스템 목적함수나 운영기간들을 고려하여 전처리함으로써 수많은 모의 발생 자료군으로부터 이산화된 확율값과 운영기간을 갖는 극히 제한된 대표 유입량을 선택한다. 선택된 대표 유입량 자료를 사용하여 확정론적 최적화 기법에 의거 이산화된 위험도나 신뢰도 수준을 갖는 기대편익을 산정하게 된다. 이와 같은 기법을 5개 저수지를 고려한 한강수계 저수지 시스템으로부터 전처리 된 평가함수별 신뢰도 수준을 갖는 발전편익 산정에 적용하였으며, 적용결과 신뢰도를 고려한 기대편익은 전형적인 Monte Carlo 기법에 의한 결과와 비슷한 수중이었으나 훨씬 적은 계산만을 요구하였다.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
• /
• pp.1033-1039
• /
• 2005

Parallel and distributed simulation is concerned with the efficient execution of large-scale discrete event simulation models on multiprocessors and distributed platforms. After the development of WWW, many efforts in the parallel and distributed simulation have been made for modeling, particularly building simulation languages and creating model libraries that can be assembled and executed over WWW. However, web-based parallel and distributed simulation is restricted by heterogeneous computing environments. Recently, the advent of XML and web services technology has made these efforts enter upon a new phase. Especially, the web services as a distributed information technology have demonstrated powerful capabilities for scalable interoperation of heterogeneous systems. This paper aims to develop and evaluate the parallel and distributed simulation using the web services technology. In particular, a prototype multi-pass simulation framework is implemented using Java-based web services technology. It focuses on the efficiency of multi-pass simulation used for optimization through the distribution of simulation replication to several simulation service providers. The development of parallel and distributed simulation using web services will help solve efficiently large-scale problems and also guarantee interoperability among heterogeneous networked systems.

• Journal of Electrical Engineering and Technology
• /
• 제8권5호
• /
• pp.991-1001
• /
• 2013

Instead of building new substations or transmission lines, proper installation of flexible AC transmission systems (FACTS) devices can make the transmission networks accommodate more power transfers with less expansion cost. In this paper, the problem to maximize power system loadability by optimally installing two types of FACTS devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), is formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). To reduce the complexity of the problem, the locations suitable for SVC and TCSC installations are first investigated with tangent vector technique and real power flow performance index (PI) sensitivity factor and, with the specified locations for SVC and TCSC installations, a set of schemes is formed. For each scheme with the specific locations for SVC and TCSC installations, the MDCP is reduced to a continuous nonlinear optimization problem and the computing efficiency can be largely improved. Finally, to cope with the technical and economic concerns simultaneously, the scheme with the biggest utilization index value is recommended. The IEEE-14 bus system and a practical power system are used to validate the proposed method.

• Industrial Engineering and Management Systems
• /
• 제8권3호
• /
• pp.171-180
• /
• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• Industrial Engineering and Management Systems
• /
• 제6권2호
• /
• pp.94-105
• /
• 2007

Measurement technology plays an important role in discrete manufacturing industry. Probe-type coordinate measuring machines (CMMs) are normally used to capture the geometry of part features. The measured points are then fit to verify a specified geometry by using the least squares method (LSQ). However, it occasionally overestimates the tolerance zone, which leads to the rejection of some good parts. To overcome this drawback, minimum zone approaches defined by the ANSI Y14.5M-1994 standard have been extensively pursued for zone fitting in coordinate form literature for such basic features as plane, circle, cylinder and sphere. Meanwhile, complex features such as torus have been left to be dealt-with by the use of profile tolerance definition. This may be impractical when accuracy of the whole profile is desired. Hence, the true deviation model of torus is developed and then formulated as a minimax problem. Next, a relatively new and simple population based evolutionary approach, particle swarm optimization (PSO), is applied by imitating the social behavior of animals to find the minimum tolerance zone torusity. Simulated data with specified torusity zones are used to validate the deviation model. The torusity results are in close agreement with the actual torusity zones and also confirm the effectiveness of the proposed PSO when compared to those of the LSQ.

• 한국농공학회논문집
• /
• 제53권6호
• /
• pp.153-163
• /
• 2011

This research describe improved algorithm that is able to decide terminal criterion of Evolutionary Structural Optimization (ESO), reducing load of calculation to search load path of concrete beam, and apply to agricultural facilities. The ESO method is that make to discrete structure, structural analyze each element stress through FEM. And repeat generation with next material condition to become for most suitable composing. Individual element introduces concept of zero stiffness, but zero stiffness decisions are gone to direction of exclusion. In this stduy, improve algorithm to be convergence by 'Rule of Alive or Die' in arrival because is most suitable. Also, existing terminal criterion lack consistency because that used depend on experience of researcher. This research procedure is fellowed. First, all modulus of elasticity assume a half of elasticity modulus of material, Second, structural analysis by FEM, Third, apply to the remove ratio and restoration ratio for the 'rule of alive or die'. Forth, reconstruct the element and material conditions. And repeat the first to forth process. The terminal time of evolutional procedure is the all elastic modulus of element changed to blank value or elasticity modulus value of original. Therefore, in this study, consist the algorithm for programming, and apply to the agricultural facilities with concrete.

• 디지털융복합연구
• /
• 제12권7호
• /
• pp.273-278
• /
• 2014

HMM(Hidden Markov Model)을 이용한 어휘 인식에서 인식 어휘의 모델들의 대한 인식 확률이 이산적인 분포를 나타내며 인식을 위한 계산량이 적은 장점이 있지만 인식률을 계산했을 때 상대적으로 낮은 단점이 있다. 이를 개선하기 위하여 HMM(Hidden Markov Model) 모델 최적화를 이용한 베이시안 기법 인식률 향상을 제안한다. 본 논문은 HMM 어휘 인식에서 인식을 위한 모델 구성을 가우시안 믹스쳐 모델로 최적화한 인식 모델을 생성하였으며 베이시안 기법인 사전확률과 사후확률을 이용한 인식률을 향상시켰다. 본 논문에서 제안한 방법을 적용한 결과 어휘인식률에서 97.9%의 인식률을 나타내었다.

• 한국복합재료학회:학술대회논문집
• /
• 한국복합재료학회 1999년도 추계학술발표대회 논문집
• /
• pp.68-72
• /
• 1999

In an effort to construct a structure under the design principle of minimal use of materials for maximum performances, a discrete gradient structure has been introduced in laminate composite systems. Using a sequential linear programming method, the gradient structure of composites to maximize the buckling load was optimized in terms of fiber volume fraction and thickness of each layer. Theoretical optimization results were then verified with experimental ones. The buckling load of laminate composite showed maximum value with the outmost [$0^{\circ}$] layer concentrated by almost all the fibers when the ratio of length to width(aspect ratio) was less than 1.0. But when the aspect ratio was 2.0, the optimum was determined in a structure where the thickness and fiber volume fraction were well balanced in each layer. From the optimization of gradient structure, the optimal fiber volume fraction and thickness of each layer were proposed. Experimental results agreed well with the theoretical ones. Gradient structures have also shown an advantage in the weight reduction of composites compared with the conventional homogeneous structures.

• 한국유체기계학회 논문집
• /
• 제17권2호
• /
• pp.48-53
• /
• 2014

A low-noise regenerative blower is developed for fuel cell application by combining the FANDAS-Regen code and design optimization algorithm under several performance constraints for flow capacity, static pressure, efficiency and power consumption. The optimized blower design model is manufactured with some impeller modification based on low noise design concept and tested by using aerodynamic performance chamber facility and narrow-band noise measurement apparatus. The measured results of the optimized blower satisfy the performance requirements and are also compared favorably with the FANDAS-Regen prediction results within a few percent relative error. Furthermore, the present study shows the remarkable noise reduction by 26 dBA can be achieved through design optimization and low noise design concept.

• 대한조선학회논문집
• /
• 제48권4호
• /
• pp.325-329
• /
• 2011

Floating, production, storage and offloading (FPSO) is a production facility that refines and saves the drilled crude oil from a drilling facility in the ocean. The flare system in the FPSO is a major part of the pressure relieving system for hydrocarbon processing plants. The flare system consists of a number of pipes and complicated connection systems. Decision of pipe support types is important since the load on the support and the stress in the pipe are influenced by the pipe support type. In this study, we optimally determined the pipe support types that minimized the support cost while satisfying the design constraints on maximum support load, maximum nozzle load and maximum pipe stress ratio. Performance indices included in the design constraints for a specified design were evaluated by pipe structural analysis using CAESAR II. Since pipe support types were all discrete design variables, an evolutionary algorithm (EA) was used as an optimizer. We successfully obtained the optimal solution that reduced the support cost by 27.2% compared to the initial support cost while all the design requirements were satisfied.