• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.899-901
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• 1998

Continuation power flow is a tool that can trace the path of the solution from the base stable solution. However, the base stable solution cannot be calculated when the initial system load is too large to operate at a stable operating point. This case is called as unsolvable case. This paper presents implementation of the optimal load shedding algorithm on continuation power flow. It performs steady-state analysis of power systems at unsolvable case that can occur in contingency analysis. Numerical simulation on 20-bus test system demonstrates that the continuation power flow applying the optimal load shedding algorithm is robust at solvable and unsolvable cases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.65-68
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• 2000

The problem of selecting a portfolio is to find Un investment plan that achieves a desired return while minimizing the risk involved. One stream of algorithms are based upon mixed integer linear programming models and guarantee an integer optimal solution. But these algorithms require too much time to apply to real problems. Another stream of algorithms are fur a near optimal solution and are fast enough. But, these also have a weakness in that the solution generated can't be guaranteed to be integer values. Since it is not a trivial job to tansform the scullion into integer valued one simutaneously maintaining the quality of the solution, they are not easy to apply to real world portfolio selection. To tackle the problem more efficiently, we propose an algorithm which generates a very good integer solution in reasonable amount of time. The algorithm is tested using Korean stock market data to verify its accuracy and efficiency.

• IE interfaces
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• v.18 no.4
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• pp.370-381
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• 2005

This study is concerned with seeking the optimal allocation(disposition) for maximizing utility of consolidating old fashioned and new air defense weapon system like SAM-X(Patriot missile) and developing efficient solution algorithm based on simulated annealing(SA) algorithm. The SED(selection by effectiveness degree) procedure is implemented with an enhanced SA algorithm in which neighboring solutions could be generated only within the optimal feasible region by using a specially designed PERTURB function. Computational results conducted on the problem sets with a variety of size and parameters shows the significant efficiency of our SED algorithm over existing methods in terms of both the computation time and the solution quality.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1721-1730
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• 2007

SThis paper proposes a new dispatch scheduling algorithm in interconnected regional system operations. The dispatch scheduling formulated as mixed integer non-linear programming (MINLP) problem can efficiently be computed by generalized Benders decomposition (GBD) algorithm. GBD guarantees adequate computation speed and solution convergency since it decomposes a primal problem into a master problem and subproblems for simplicity. In addition, the inter-temporal optimal power flow (OPF) subproblem of the dispatch scheduling problem is comprised of various variables and constraints considering time-continuity and it makes the inter-temporal OPF complex due to increased dimensions of the optimization problem. In this paper, regional decomposition technique based on auxiliary problem principle (APP) algorithm is introduced to obtain efficient inter-temporal OPF solution through the parallel implementation. In addition, it can find the most economic dispatch schedule incorporating power transaction without private information open. Therefore, it can be expanded as an efficient dispatch scheduling model for interconnected system operation.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.105-116
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• 1989

This study presents an algorithm that determines the optimal configuration of the FMSs with limited local buffers. The algorithm finds the lowest cost configuration, i.e. the number of tools, the number of pallets as well as the number of buffers to be installed in front of each machine in the system. Thus it assures a given production ratio with a minimum cost. In the algorithm, FMSs are considered as the closed queueing network with limited queue length. System performance evaluation is performed using the Block-&-Recirculation model developed by Yao and Buzacott. The algorithm is composed with three steps. The steps are namely i) determination of a lower configuration, ii) derivation of an heuristic solution, and iii) obtaining the optimal solution. The computational efforts required in the algorithm usually lies within the capability of personal computers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.221-227
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• 2019

It has long been known that weapon target assignment (WTA) problem is NP-hard. Nonetheless, an exact solution can be found using Brute-Force or branch-and bound method which utilize approximation. Many heuristic algorithms, genetic algorithm particle swarm optimization, etc., have been proposed which provide near-optimal solutions in polynomial time. This paper suggests polynomial time algorithm that can be obtain the optimal solution of WTA problem for the number of total weapons k, the number of weapon types m, and the number of targets n. This algorithm performs k times for O(mn) so the algorithm complexity is O(kmn). The proposed algorithm can be minimize the number of trials than brute-force method and can be obtain the optimal solution.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.101-106
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• 2015

This paper suggests heuristic algorithm with polynomial time complexity for rigging elections problem that can be obtain the optimal solution using linear programming. The proposed algorithm transforms the given problem into adjacency graph. Then, we divide vertices V into two set W and D. The set W contains majority distinct and the set D contains minority area. This algorithm applies divide-and-conquer method that the minority area D is include into majority distinct W. While this algorithm using simple rule, that can be obtains the optimal solution equal to linear programing for experimental data. This paper shows polynomial time solution finding rule potential in rigging elections problem.

• ETRI Journal
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• v.31 no.5
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• pp.534-544
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• 2009

Finding link-disjoint or node-disjoint paths under multiple constraints is an effective way to improve network QoS ability, reliability, and so on. However, existing algorithms for such scheme cannot ensure a feasible solution for arbitrary networks. We propose design principles of an algorithm to fill this gap, which we arrive at by analyzing the properties of optimal solutions for the multi-constrained link-disjoint path pair problem. Based on this, we propose the link-disjoint optimal multi-constrained paths algorithm (LIDOMPA), to find the shortest link-disjoint path pair for any network. Three concepts, namely, the candidate optimal solution, the contractive constraint vector, and structure-aware non-dominance, are introduced to reduce its search space without loss of exactness. Extensive simulations show that LIDOMPA outperforms existing schemes and achieves acceptable complexity. Moreover, LIDOMPA is extended to the node-disjoint optimal multi-constrained paths algorithm (NODOMPA) for the multi-constrained node-disjoint path pair problem.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.97-100
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• 1987

An improved hydrothermal unit commitment algorithm is proposed for the purpose of optimal operation of electric power system. Especially, Dynamic Programming Method which is main scheme of the algorithm is modified to assure the feasible solution all the time. The effectiveness of the algorithm has been demonstrated by applying to a sample system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.225-228
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• 2001

DNA computing has been applied to the problem of getting an optimal solution since Adleman's experiment. DNA computing uses strings with various length and four-type bases that makes more useful for finding a global optimal solutions of the complex multi-modal problems. This paper presents DNA coding method for finding optimal solution of the multi-modal function and compares the efficiency of this method with the genetic algorithms (GA). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string and DNA coding method uses a tool of calculation or Information store with DNA molecules and four-type bases denoted by the symbols of A(Ademine), C(Cytosine), G(Guanine) and T(Thymine). The same operators, selection, crossover, mutation, are applied to the both DNA coding algorithm and genetic algorithms. The results show that the DNA based algorithm performs better than GA.