• Bulletin of the Korean Mathematical Society
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• v.26 no.2
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• pp.127-134
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• 1989

This paper proposes a deformation method for solving practical nonlinear programming problems. Utilizing the nonlinear parametric programming technique with Quasi-Newton method [6,7], the method solves the problem by imbedding it into a suitable one-parameter family of problems. The approach discussed in this paper was originally developed with the aim of solving a system of structural optimization problems with frequently appears in various kind of engineering design. It is assumed that we have to solve more than one structural problem of the same type. It an optimal solution of one of these problems is available, then the optimal solutions of thel other problems can be easily obtained by using this known problem and its optimal solution as the initial problem of our parametric method. The method of nonlinear programming does not generally converge to the optimal solution from an arbitrary starting point if the initial estimate is not sufficiently close to the solution. On the other hand, the deformation method described in this paper is advantageous in that it is likely to obtain the optimal solution every if the initial point is not necessarily in a small neighborhood of the solution. the Jacobian matrix of the iteration formula has the special structural features [2, 3]. Sectioon 2 describes nonlinear parametric programming problem imbeded into a one-parameter family of problems. In Section 3 the iteration formulas for one-parameter are developed. Section 4 discusses parametric approach for Quasi-Newton method and gives algorithm for finding the optimal solution.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.148-155
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• 2005

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• Journal of applied mathematics & informatics
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• v.7 no.3
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• pp.787-800
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• 2000

In this paper we consider an optimal control system described by n-dimensional heat equation with a thermal source. Thus problem is to find an optimal control which puts the system in a finite time T, into a stationary regime and to minimize a general objective function. Here we assume there is no constraints on control. This problem is reduced to a moment problem. We modify the moment problem into one consisting of the minimization of a positive linear functional over a set of Radon measures and we show that there is an optimal measure corresponding to the optimal control. The above optimal measure approximated by a finite combination of atomic measures. This construction gives rise to a finite dimensional linear programming problem, where its solution can be used to determine the optimal combination of atomic measures. Then by using the solution of the above linear programming problem we find a piecewise-constant optimal control function which is an approximate control for the original optimal control problem. Finally we obtain piecewise-constant optimal control for two examples of heat equations with a thermal source in one-dimensional.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.220-223
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• 2003

This paper presents VSCOPF(Votage Stability Constrained Optimal Power Flow) algorithm based on SLP(Successive Linear Programming) to interpret the large scale system. Voltage stability index used to this paper is L index to be presented by function form. The objective function consists of load shedding cost minimization. Voltage stability indicator constraint was incorporated in traditional OPF formulation. as well as the objective function and constraints are linearlized and the optimal problem is performed by SLP(Successive Linear Programming). In this paper, the effect of voltage stability limit constraint is showed in the optimal load curtailment problems. As a result, an optimal solution is calculated to minimize load shedding cost guaranteeing voltage security level. Numerical examples using IEEE 39-bus system is also presented to illustrate the capabilities of the proposed formulation.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.3
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• pp.313-319
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• 2002

Since the oil crisis in 1970, a great deal of effort has been made to develop automatic electric load sharing systems as a part of the efforts to save energy. A large scale electric generating system composes more than two generators whose characteristics may be different. When such a system is operated individually or in parallel, the lagrange multiplier's method has difficulty in achieving optimal load distribution because generators usually have the limitations of the operating range with inequality constraints. Therefore, a suitable operating mode of generators has to be decided according to the selection of the generators to meet electric power requirements at the minimum cost. In this study, a method which solves the optimal electric load distribution problem using the dynamic programming technique is proposed. This study also shows that the dynamic programming method has an advantage in dealing with the optimal load distribution problem under the limitations of the operating range with inequality constraints including generator operation mode. In this study, generator operating cost curve of second order equation by shop trial test results of diesel generators are used. The results indicate that the proposed method can be applied to the ship's electric generating system.

• IE interfaces
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• v.1 no.1
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• pp.17-26
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• 1988

This paper describes a nonlinear goal programming approach to the optimal composition of composite solid propellant taking multiple characteristics into consideration synchronously. The nonlinear goal programming model with response functions, restrictions and the optimal value of each characteristic is developed using Scheffe's "Experiments with mixtures" and preference weighting system. Objective functions are described based on process, performance and assurance characteristics. The systematic approach to optimal composition in this study is proved efficient through a CTPB-AL-AP propellant which is one of composite solid propellant systems.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1157-1165
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• 2011

The Karush-Kuhn-Tucker (KKT) necessary optimality conditions for nonlinear differentiable programming problems are also sufficient under suitable convexity assumptions. The KKT conditions in multiobjective programming problems with interval-valued objective and constraint functions are derived in this paper. The main contribution of this paper is to obtain the Pareto optimal solutions by resorting to the sufficient optimality condition.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.81-94
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• 1986

A shortest path dynamic programming formulation is proposed and attemped to solve an uncapacitated expansion sequencing problem. It is also compared with the Extended Binary State Space approach with total capacity. Difficulties and merits associated with the formulation are discussed. The shortest path dynamic programming lacks the separability condition and an optimal solution is not guaranteed. However it has other merits and seems to be the practical solution procedure for the expansion sequencing problem in a sense that it finds near optimal solution with less state evaluations.