• 전기학회논문지
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• 제62권10호
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• pp.1349-1353
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• 2013

The optimal analysis has objective functions, equality constraint functions and inequality functions. Objective functions may be used with inequality function, because occasionally variables are moved to non-analytic condition with calculating objective functions. But inequality constraint functions are very complicated problem in a optimal analysis. this paper suggest a method to solve inequality constraint functions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.197-199
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• 1999

This paper deals with optimal power flow, which is optimal problem with equality constraint and inequality constraint. A algorithm of changing two constraints problem to one constraint - equality constraint problem - that make it analytical access for optimal power flow is presented.

• Nuclear Engineering and Technology
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• 제16권4호
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• pp.181-194
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• 1984

변분법을 사용하여 원자로의 핵연료 관리문제를 연구하였다. 원자력 발전소에 영향을 미치는 두 함수 즉 이윤함수와 가격함수는 원자로의 연소도방정식과 최대허용출력 밀도에 대한 부등 제약조건이며, 이들은 임계성의 제약조건이 된다. 초기이윤의 변분해는 원자로에 뚜렷한 두 영역이 있음을 보여 주었다. 즉 일정 출력 영역과 최소 재고량 또는 평활 중성자속 영역이 그것이다. 이들 든 영역의 변이점은 전력에 대한 이윤과 연료에 대한 이자 지급에 상당히 중요하다. 그러므로 각 영역에서 동일 농축도의 핵연료를 가질 동일 부피의 세 영역으로 된 원자로를 최적화 하기 위하여 핵연료 주기 가격 함수가 사용 되었다. 최대 허용 출력 밀도에 대한 부등 제약조건들은 이들 부등 제약 조건이 원자로심의 어느 특정 점이나 로심주기를 통하여 항상 동일 제약조건이 되어야 한다. 원자로의 임계성과 출력밀도에 대한 동일 제약조건에 관계된 핵연료의 연소도에 대한 계차 방정식의 해를 구하였으며 최적 농축도의 위치를 구하기-위하여 구배법을 사용하였다. 이들 계산결과는 부동 제약 조건들을 적절히 적용하면 원자로를 최적화하기 위하여 비선형 최적 기술이 사용될 수 있음을 보여 주었다.

• Journal of Mechanical Science and Technology
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• 제14권6호
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• pp.655-665
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• 2000

We propose an efficient algorithm for the purpose of satisfying a wide range of design constraints represented with equality and inequality equations as well as production rules. The algorithm employs simulated-annealing and a production rule inference engine and works on design constraints represented with networks. The algorithm fulfills equality constraints through constraint satisfaction processes like variable elimination while taking into account inequality constraints and inferring production rules. It can also reduce the load of the optimization procedure if necessary. We demonstrate the implementation of the algorithm with the result on machine tool design.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1099-1109
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• 2018

For practical consideration, economic dispatch (ED) problems in power system have non-smooth cost functions with equality and inequality constraints that makes the problems complex constrained nonlinear optimization problems. This paper proposes a new constraint handling method for equality and inequality constraints which is employed to solve ED problems, where the incremental rate is employed to enhance the modification process. In order to prove the applicability of the proposed method, the study cases are tested based on the classical particle swarm optimization (PSO) and differential evolution (DE) algorithm. The proposed method is evaluated for ED problems using six different test systems: 6-, 15-, 20-, 38-, 110- and 140-generators system. Simulation results show that it can always find the satisfactory solutions while satisfying the constraints.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.589-594
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• 한국정밀공학회지
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• 제14권9호
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• pp.116-123
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.141-144
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• 2007

Given a number of training data, a traditional BPN is normally trained by minimizing the absolute difference between target outputs and approximate outputs. When BPN is used as a meta-model for inequality constraint function, approximate optimal solutions are sometimes actually infeasible in a case where they are active at the constraint boundary. The paper describes the development of the efficient BPN based meta-model that enhances the constraint feasibility of approximate optimal solution. The modified BPN based meta-model is obtained by including the decision condition between lower/upper bounds of a constraint and an approximate value. The proposed approach is verified through a simple mathematical function and a ten-bar planar truss problem.

• 제어로봇시스템학회논문지
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• 제11권1호
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• pp.13-18
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• 2005

This paper considers a design problem of the repetitive control system for linear systems with time-varying norm bounded uncertainties. Using the Lyapunov functional for time-delay systems, a sufficient condition ensuring robust stability of the repetitive control system is derived in terms of an algebraic Riccati inequality (ARI) or a linear matrix inequality (LMI). Based on the derived condition, we show that the repetitive controller design problem can be reformulated as an optimization problem with an LMI constraint on the free parameter.

• Management Science and Financial Engineering
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• 제14권1호
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• pp.91-96
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• 2008

Robust knapsack problem appears when dealing with data uncertainty on the knapsack constraint. This note presents a generalization of the cover inequality for the problem with its lifting procedure. Specifically, we show that the lifting can be done in a polynomial time as in the usual knapsack problem. The results can serve as a building block in devising an efficient branch-and-cut algorithm for the general robust (0, 1) IP problem.