• 전자공학회논문지B
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• 제31B권7호
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• pp.179-189
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• 1994

A two-phase neural network finds exact feasible solutions for a constrained optimization programming problem. The time-varying programming neural network is a modified steepest-gradient algorithm which solves time-varying optimization problems. In this paper, we propose a time-varying two-phase optimization neural network which incorporates the merits of the two-phase neural network and the time-varying neural network. The proposed algorithm is applied to system identification and function approximation using a multi-layer perceptron. Particularly training of a multi-layer perceptrion is regarded as a time-varying optimization problem. Our algorithm can also be applied to the case where the weights are constrained. Simulation results prove the proposed algorithm is efficient for solving various optimization problems.

• Computers and Concrete
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• 제18권2호
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• pp.155-163
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• 2016

This paper, proposes 20 models for predicting compressive strength of recycled aggregate concrete (RAC) containing silica fume by using gene expression programming (GEP). To construct the models, experimental data of 228 specimens produced from 61 different mixtures were collected from the literature. 80% of data sets were used in the training phase and the remained 20% in testing phase. Input variables were arranged in a format of seven input parameters including age of the specimen, cement content, water content, natural aggregates content, recycled aggregates content, silica fume content and amount of superplasticizer. The training and testing showed the models have good conformity with experimental results for predicting the compressive strength of recycled aggregate concrete containing silica fume.

• 한국국방경영분석학회지
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• 제27권2호
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• pp.37-55
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• 2001

The main purpose of this study is to review the current system and to develop a decision support system for evaluating the priorities among those possible alternatives in the army facility enterprise. This paper also provides an information system which can be effectively applied to various criteria and stages in decision making process such as Planning and Programming phases in PPBEES. The model base of decision support systems uses the concepts of the analytic hierarchy process along with the supplementary techniques such as TOPSIS and 0-1 integer programming. Both AHP and TOPSIS are used scoring approaches in the Planning phase and IP is induced at the Programming phase to give GO/NO-GO solution for each project. We use Expert Choice, Excel and LINDO s/w's to implement a prototyped model. The proposed methodology in this paper enables the decision makers to evaluate the priority based on quantitative and qualitative data in a systematic way.

• 한국정보통신학회논문지
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• 제7권6호
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• pp.1351-1359
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• 2003

극한 프로그래밍은 빠르게 변화되는 사업 환경에 기민하게 대응하는 애자일 소프트웨어 개발 방법론 중에서 가장 대표적인 방법론이다. 소프트웨어 산업이 성숙됨에 따라 소프트웨어 품질 요소중 사용성이 점차 강조되고 있으나, 극한 프로그래밍에서 사용성을 확보하기 위한 노력이 부족한 실정이다. 극한 프로그래밍의 사용성 향상을 위하여 본 논문에서는 소프트웨어 생명주기를 조사, 계획, 릴리즈 반복, 제품화, 유지보수, 사망의 6단계로 정의한다. 사용성 평가를 위한 통합시험과 인수시험을 포함한 11개의 활동을 정의하여 사용성을 향상시킬수 있는 극한 프로그래밍 프로세서를 제안한다. 제안한 프로세서의 타당성을 4가지 측면에서 확인하였다. 제안한 프로세스는 극한 프로그래밍 프로세스가 인수시험 활동을 지원하도록 개선하였으며, 극한 프로그래밍 프로세스가 CMM 레벨4를 지원하도록 하며, CMM 품질보증 실무를 지원하도록 하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.262-263
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• 2006

This paper presents a scheme to solve the congestion problem with phase-shifting transformer(PST) and power generation using linear programming method. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. linear programming method is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow. The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.137-141
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• 1986

This paper presents optimal recursive digital filter design to meet simultaneous specifications of magnitude and linear phase characteristics. As is well known, the overshoot in the vicinity of discontinuity is hight. The technique using linear programming (the dual programming) is choosing more specification points in the vicinity of band limit frequency. The resulting filter can shown improved response and numerical accuracy with reduced nonuniform specification points in frequency domain.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• 산업경영시스템학회지
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• 제28권2호
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• pp.94-100
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• 2005

This paper presents the application of integrated mathematical programming approach for the design of cellular manufacturing. The proposed approach is carried out in two phases The first phase concerning exceptional elements(EEs) in cell formation and the second phase facilities layout design. This paper considers the total costs of three important costs for (1) intercellular transfer (2) machine duplication and (3) subcontracting. One of Important issue is the calculation of the number of machines considering the maximum utilization of machines and the available capacity of a machines that can be transferred between cells. Facilities layout design is considered to reflect the real field data taking in to account the operational sequence of the parts to be manufactured. The model is formulated as mixed integer programming that is employed to find the optimal solution.

• 한국국방경영분석학회지
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• 제30권1호
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• pp.1-14
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• 2004

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.

• 전기의세계
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• 제30권6호
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• pp.375-385
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• 1981

New algorithms are derived for nonlinear programming problems which are characterized by their large variables and equality and inequality constraints. The algorithms are based upon the introduction of the Dependent-Variable-Elimination method, Independent-Variable-Reduction method, Optimally-Ordered-Triangular-Factorization method, Equality-Inequality-Sequential-Satisfaction method, etc. For a case study problem relating to the optimal determination of load flow in a 10-bus, 13-line sample power system, several approaches are undertaken, such as SUMT, Lagrange's Multiplier method, sequential applications of linear and quadratic programming method. For applying the linear programming method, the conventional simplex algorithm is modified to the large-system-oriented one by the introduction of the Two-Phase method and Variable-Upper-Bounding method, thus resulting in remarkable savings in memory requirements and computing time. The case study shows the validity and effectivity of the algorithms presented herein.