• Journal of Advanced Marine Engineering and Technology
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• 제37권7호
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• pp.743-751
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• 2013

In this paper, an approach to deal with model uncertainty using norm-optimal iterative learning control (ILC) is mentioned. Model uncertainty generally degrades the convergence and performance of conventional learning algorithms. To deal with model uncertainty, a worst-case norm-optimal ILC is introduced. The problem is then reformulated as a convex minimization problem, which can be solved efficiently to generate the control signal. The paper also investigates the relationship between the proposed approach and conventional norm-optimal ILC; where it is found that the suggested design method is equivalent to conventional norm-optimal ILC with trial-varying parameters. Finally, simulation results of the presented technique are given.

• 한국국방경영분석학회지
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• 제27권1호
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• pp.28-38
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• 2001

A transportation problem amy have multiple optimal solutions, if an optimal solution to the problem is degenerate. This study derives a condition, under which multiple degenerate optimal solutions exist, fro ma current degenerate optimal transportation tableau by utilizing the homogeneous equation obtained from the closed loops connecting degenerate basic variable and non-basic variables, and discusses a method of generating alternative degenerate optimal solutions and their associated transportation tableaus. Each degenerate optimal solution may not have the same range of feasibility in sensitivity analysis on supply and demand quantity due to different set of shadow prices which multiple degenerate solution have.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.111-116
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• 2000

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on tow steps. The first step transforms optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPB(two point boundary condition problem) is solved by algebraic equations instead of differential equations using BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems. In computer simulation, the algorithm was verified through the optimal control design of Van del pole system and Volterra Predatory-prey system.

• 대한산업공학회지
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• 제1권1호
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• pp.79-86
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• 1975

The optimal time-sequential distribution of supporting fire against enemy ground units in combat against attacking friendly units is studied. Lanchester type models of warfare are combined with optimal control theory in this investigation. The optimal time-sequential fire-support policy is characterized for a specific problem. Although complete details for the determination of the optimal policy are not given, it is conjectured, on the basis of the theorems which were proved, that for this problem the optimal policy is to always concentrate all supporting fire on the same enemy unit until supporting fire must be lifted.

• East Asian mathematical journal
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• 제22권2호
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• pp.171-188
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• 2006

We consider the problem of an optimal control of the wave equation with a localized nonlinear dissipation. An optimal control is used to bring the state solutions close to a desired profile under a quadratic cost of control. We establish the existence of solutions of the underlying initial boundary value problem and of an optimal control that minimizes the cost functional. We derive an optimality system by formally differentiating the cost functional with respect to the control and evaluating the result at an optimal control.

• Journal of applied mathematics & informatics
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• 제30권5_6호
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• pp.719-728
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• 2012

In this paper, we develop a numerical method to solving an optimal control problem, which is governed by a parabolic partial differential equations(PDEs). Our approach is to approximate the PDE problem to initial value problem(IVP) in $\mathbb{R}$. Then, the homogeneous part of IVP is solved using semigroup theory. In the next step, the convergence of this approach is verified by properties of one-parameter semigroup theory. In the rest of paper, the original optimal control problem is solved by utilizing the solution of homogeneous part. Finally one numerical example is given.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.131-138
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• 2016

In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

• 대한전기학회논문지:전력기술부문A
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• 제54권12호
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• pp.597-602
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• 2005

The introduction of competition in electricity market emphasizes the importance of sufficient transmission capacities to guarantee various electricity transactions. Therefore, when dispatch scheduling, transmission security constraints should be considered for the economic and stable electric power system operation. In this paper, we propose an optimal dispatch scheduling algorithm incorporating transmission security constraints. For solving these constraints, the dispatch scheduling problem is decomposed into a master problem to calculate a general optimal power flow (OPF) without transmission security constraints and several subproblems to inspect the feasibility of OPF solution under various transmission line contingencies. If a dispatch schedule given by the master problem violates transmission security constraints, then an additional constraint is imposed to the master problem. Through these iteration processes between the master problem and subproblems, an optimal dispatch schedule reflecting the post-contingency rescheduling is derived. Moreover, since interruptible loads can positively participate as generators in the competitive electricity market, we consider these interruptible loads active control variables. Numerical example demonstrates efficiency of the proposed algorithm.

• 경영과학
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• 제15권1호
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• pp.77-85
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• 1998

In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solutions of a multiple objective linear program. Since the efficient set is in general a nonconvex set, problem (P) can be classified as a global optimization problem. Perhaps due to its inherent difficulty, relatively few attempts have been made to solve problem (P) in spite of the potential benefits which can be obtained by solving problem (P). The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.209-224
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• 2006

This paper presents an optimization model with performance constraints for two kinds of graph elements layout problem. The layout problem is partitioned into finite subproblems by using graph theory and group theory, such that each subproblem overcomes its on-off nature about optimal variable. Furthermore each subproblem is relaxed and the continuity about optimal variable doesn't change. We construct a min-max problem which is locally equivalent to the relaxed subproblem and develop the first order necessary and sufficient conditions for the relaxed subproblem by virtue of the min-max problem and the theories of convex analysis and nonsmooth optimization. The global optimal solution can be obtained through the first order optimality conditions.