• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.141-157
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• 2004

In this paper, we consider broadband satellite systems using MF-TDMA(Multi-Frequency Time Division Multiple Access) scheme. First, we analyze return link, superframe structure, and QoS( Quality of Service) parameters in broadband satellite systems, and mathematically formulate the QoS-based optimal timeslot allocation problem as a nonlinear integer programming problem for broadband satellite systems with clear-sky and rain-fade satellite terminals, and multiple data classes. Next, we modify the proposed problem to solve it within in a fast time, and suggest the QoS-based optimal timeslot allocation scheme. Extensive simulation results show that the proposed scheme finds an optimal solution or a near optimal solution within 5ms at Pentium IV PC.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.161-168
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• 2014

The optimal solution of minimum cost for aircraft landing problem(ALP) is very difficult problem because the approached aircraft are random time interval. Therefore this problem has been applied by various meta heuristic methods. This paper suggests O(nlog n) polynomial time heuristic algorithm to obtain the optimal solution for ALP. This algorithm sorts the target time of aircraft into ascending order. Then we apply the optimization of change the landing sequence take account of separation time and the cost of landing. For the Airland1 through Airland8 of benchmark data of ALP, we choose 25 data until the number of runway m that the total landing cost is 0. We can be obtain the optimal solution for all of the 25 data. Especially we can be improve the known optimal solution for m = 1of Airland8.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.139-147
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• 2012

This paper suggests simple search algorithm for optimal solution in assignment problem. Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm. The proposed algorithm reduces the 4 steps of Hungarian algorithm to 1 step, and only selects the minimum cost of row and column then gets the optimal solution simply. For the 27 balanced and 7 unbalanced assignment problems, this algorithm finds the optimal solution but the genetic algorithm fails to find this values. This algorithm improves the time complexity O($n^3$) of Hungarian algorithm to O(n). Therefore, the proposed algorithm can be general algorithm for assignment problem replace Hungarian algorithm.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.83-94
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• 2001

In this paper, the consumable spare parts requirement determination problem of newly procured equipment systems is considered. The problem is formulated as the cost minimization problem with operational availability constraint. Assuming part failure rate is constant during operational period, an analytical method is developed to obtain spare part requirements. Since this solution tends to overestimate the requirements, a fast search simulation procedure is introduced to adjust it to the realistic solution. The analytical solution procedure and the simulation procedure are performed recursively until a near optimal solution is achieved. The experimental results show that the near optimal solution is approached in a fairly short amount of time.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.211-218
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• 1998

As a part of trajectory modulation to increase system survivability and terminal effectiveness, impact angle control is required in the terminal phase of tactical missile systems. The missile systems are not allowed to have high altitude to reduce probability of detection by sensors of missile defense systems. In this paper, an analytic form of a time-optimal control law is suggested in the case of constrained missile maneuverability and impact angle under the assumption of a zero-lag autopilot. The control law is obtained by establishing optimal missile-target engagement geometry in the vertical plane. Extension of the law for missiles with autopilot response lags requiring a numerical solution is studied by introducing an iterative algorithm for optimal switching time determination of which the initial switching instants are obtained from the analytic solution. Also suggested is a closed-form impact angle control law derived by an energy-optimal approach. The performances of the proposed guidance laws are evaluated by a series of computer runs.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.432-435
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• 1995

In this paper a new approach to obtain the solution of the linear-quadratic Gaussian control problem for singularly perturbed discrete-time stochastic systems is proposed. The alogorithm proposed is based on exploring the previous results that the exact solution of the global discrete algebraic Riccati equations is found in terms of the reduced-order pure-slow and pure-fast nonsymmetric continuous-time algebraic Riccati equations and, in addition, the optimal global Kalman filter is decomposed into pure-slow and pure-fast local optimal filters both driven by the system measurements and the system optimal control input. It is shown that the optimal linear-quadratic Gaussian control problem for singularly perturbed linear discrete systems takes the complete decomposition and parallelism between pure-slow and pure-fast filters and controllers.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.91-98
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• 1990

This paper studies a heuristic method for the Maximum Origin-Destination Flow Path (MODFP) in an acyclic transportation network. We construct a mathematical formulation for finding the MODFP. Then by applying Benders' partitioning method, we generate two subproblems which should be solved in turn so that they may give an optimal solution. We solve one subproblem by an optimal seeking algorithm and the other by a hueristic method. so that, we finally obtain a good solution. The computational complexity of calculating the optimal solution of the first subproblem is 0(mn) and that of calculating the heuristic solution of the other subproblem is $0(n^2).$ From the computational experiments, we estimated the performance of the heuristic method as being 99.3% and the computing time relative to optimal algorithm as being 28.76%.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.183-194
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• 2003

We will explain a new method for obtaining the nearly optimal domain for optimal shape design problems associated with the solution of a nonlinear wave equation. Taking into account the boundary and terminal conditions of the system, a new approach is applied to determine the optimal domain and its related optimal control function with respect to the integral performance criteria, by use of positive Radon measures. The approach, say shape-measure, consists of two steps; first for a fixed domain, the optimal control will be identified by the use of measures. This function and the optimal value of the objective function depend on the geometrical variables of the domain. In the second step, based on the results of the previous one and by applying some convenient optimization techniques, the optimal domain and its related optimal control function will be identified at the same time. The existence of the optimal solution is considered and a numerical example is also given.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.169-175
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• 2021

The lot sizing problem(LSP) is a hard problem that classified as non-deterministic(NP)-complete because of the polynomial-time optimal solution algorithm is unknown yet. The well-known W-W algorithm can be obtain the solution within polynomial-time, but this algorithm is a very complex, therefore the heuristic approximated S-M algorithm is suggested. This paper suggests O(n) linear-time complexity algorithm that can be find not the approximated but optimal solution. This algorithm determines the lot size Xt∗ in period t to the sum of the demands of interval [t,t+k], the period t+k is determined by the holding cost will not exceed setup cost of t+k period. As a result of various experimental data, this algorithm finds the optimal solution about whole data.

• 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.