• Computers and Concrete
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• 제6권3호
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• pp.253-268
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• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• 한국전산유체공학회지
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• 제11권2호
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• pp.19-24
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• 2006

A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.475-480
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• 1997

In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making fur both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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• pp.173-183
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• 2018

Purpose: It is critical to design a set of experiments in Test and Evaluation Process for a weapon system. Because there is no sufficient resources in real-world, one must choose a subset of experiments which is considered to be more important. Methods: We introduce an optimization model for choosing the subset of experiments by considering a priority of experimental variable and level and restrictions of resources. We describe in detail how we construct objective function and constraints which must be a right realization of our logic and assumption. Conclusion: Since our optimization model turns out to be computationally difficult to solve, we introduce an algorithm for reducing the size of problem. Various computational results follows.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.1912-1931
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• 2018

In future wireless network, user experience and energy efficiency will play more and more important roles in the communication systems compared to their roles at present. Quality of experience (QoE) and Energy Efficiency (EE) become the widely used metrics. In this paper, we study a combinatorial problem of QoE and EE and investigate a fair power allocation in heterogeneous networks. We first design a new metric, QoE-aware EE (QEE) to reflect the relationship of QoE and energy. Then, the concept of Utopia QEE is introduced, which is defined as the achievable maximum QEE in ideal conditions, for each user. Finally, we transform the power allocation process to an optimization of ratio of QEE and Utopia QEE and use invasive weed optimization (IWO) algorithm to solve the optimization problem. Numerical simulation results indicate that the proposed algorithm can get converged and efficiently improve the system energy efficiency and the QoE for each user.

• 한국전산구조공학회논문집
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• 제21권4호
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• pp.317-324
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• 2008

대형 구조물에 대한 최적설계를 고려할 때 구조해석에 많은 시간과 노력이 소비된다. 한대의 개인용 컴퓨터에 의한 대형 구조물의 구조해석은 대용량의 기억장치와 많은 계산시간이 요구되므로 반복적 해석이 필요한 대형 구조물의 설계에 효율적으로 이용되기 어렵다. 따라서 본 논문에서는 이러한 문제의 대안으로 인터넷이 연결된 다수의 개인용 컴퓨터들로 고성능 병렬연산시스템을 구성하여 구조해석을 분산 처리하여 계산시간을 절감하였다. 아울러 반응표면의 근사를 위해 요구되는 구조해석을 상용 구조해석 어플리케이션으로 해결할 수 있다면 상용성이 확보되어 일반 구조물에 대하여도 반응표면법을 이용한 최적설계를 수행할 수 있을 것이다.

• KIEE International Transaction on Systems and Control
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• 제12D권1호
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• pp.17-26
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• 2002

In this paper, a new design methodology of the fuzzy controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors. The design procedure is based on evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm to adjust and estimate scaling factors respectively. The tuning of the soiling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as HCM (Hard C-Means) and Neuro-Fuzzy model[7]. The validity and effectiveness of the proposed estimation algorithm for the fuzzy controller are demonstrated by the inverted pendulum system.

• 한국컴퓨터정보학회논문지
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• 제21권2호
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• pp.71-77
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• 2016

There has been unknown polynomial time algorithm for cellular formation problem (CFP) that is one of the NP-hard problem. Therefore metaheuristic method has been applied this problem to obtain approximated solution. This paper shows the existence of polynomial-time heuristic algorithm in CFP. The proposed algorithm performs coarse-grained and fine-grained cell formation process. In coarse-grained cell formation process, the cell can be formed in accordance with machine frequently used that is the number of other products use same machine with special product. As a result, the machine can be assigned to most used cell. In fine-grained process, the product and machine are moved into other cell that has a improved grouping efficiency. For 35 experimental data, this heuristic algorithm performs better grouping efficiency for 12 data than best known of meta-heuristic methods.

• 한국공간구조학회:학술대회논문집
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• 한국공간구조학회 2008년도 춘계 학술발표회 논문집
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• pp.101-106
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• 2008

본 연구에서는 서로 상이한 최적화기법인 유전알고리듬과 수학적 프로그래밍기법을 이용하여 지오데식 돔 구조물을 최적화하고 그 결과를 분석하였다. 본 연구에서 도입한 유전알고리즘은 유전연산자인 선택, 교배, 돌연변이 이외에도 재생기법을 도입하여 최적해의 검색성능을 높였다. 그리고 수학적인 프로그래밍기법은 유한차분법을 이용하여 목적함수의 설계민감도를 계산하였으며 세 가지의 다른 검색기법을 이용하여 돔의 크기최적화를 수행하였다. 지오데식 돔의 중앙에 작용하는 집중하중에 저항하는 돔의 각 부재의 크기패턴을 자체 개발된 $ISADO-GA{\alpha}$와 ISADO-OPT를 이용하여 최적 설계하였다. 본 연구를 통하여 제시된 최적결과는 정해가 존재하지 않는 실제 구조물의 최적 값에 대한 유용한 정보를 제공할 뿐만이 아니라 향후 대공간구조의 새로운 구조시스템 개발의 밑거름이 될 것으로 판단된다.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2006년도 정기학술발표대회 논문집
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• pp.511-514
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• 2006

자재 관리는 건설프로젝트에서 소요되는 전체 비용의 50%이상에 해당하는 가장 중요한 현장 관리 중 하나이다. 건설 분야의 자재 관리 방법 증 하나로 무선 주파수 인식(Radio Frequency Identification)을 사용한 관리가 시도되고 있다. 하지만 현재 RFID의 트랜스폰더(Transponder)를 어떻게 그리고 어디에 설치하여야 효율적인 자재 관리가 이루어지는 지에 대한 연구가 미비한 실정이고 어떠한 방법으로 최적화를 하여야 효율적인 설치가 될 것인지에 대한 연구도 이루어 지지 않고 있다. 따라서 본 연구에서는 RFID 트랜스폰더를 공사 현장에서 어떻게 그리고 어디에 설치하여야 효율적인 위치 설정이 될 수 있는지 유전자 알고리즘(Genetic Algorithm)을 이용한 최적화 방법에 대하여 알아본다.