• Journal of Electrical Engineering and Technology
• /
• v.12 no.6
• /
• pp.2187-2195
• /
• 2017

In order to solve the AC optimal power flow (OPF) problem considering the generators' on/off status, it is necessary to model the problem as mixed-integer nonlinear programming (MINLP). Because the computation time to find the optimal solution to the mixed-integer AC OPF problem increases significantly as the system becomes larger, most of the existing solutions simplify the problem either by deciding the on/off status of generators using a separate unit commitment algorithm or by ignoring the minimum output of the generators. Even though this kind of simplification may make the overall computation time tractable, the results can be significantly erroneous. This paper proposes a novel algorithm for the mixed-integer AC OPF problem, which can provide a near-optimal solution quickly and efficiently. The proposed method is based on a combination of the outer approximation method and the relaxed AC OPF theory. The method is applied to a real-scale power system that has 457 generators and 2132 buses, and the result is compared to the branch-and-bound (B&B) method and the genetic algorithm. The results of the proposed method are almost identical to those of the compared methods, but computation time is significantly shorter.

• Advances in aircraft and spacecraft science
• /
• v.9 no.5
• /
• pp.433-447
• /
• 2022

This work deals with an explicit guidance and control architecture for autonomous lunar ascent and orbit injection, i.e., the locally-flat near-optimal guidance, accompanied by nonlinear reduced-attitude control. This is a new explicit guidance scheme, based on the local projection of the position and velocity variables, in conjunction with the real-time solution of the associated minimum-time problem. A recently-introduced quaternion-based reduced-attitude control algorithm, which enjoys quasi-global stability properties, is employed to drive the longitudinal axis of the ascent vehicle toward the desired direction. Actuation, based on thrust vectoring, is modeled as well. Extensive Monte Carlo simulations prove the effectiveness of the guidance, control, and actuation architecture proposed in this study for precise lunar orbit insertion, in the presence of nonnominal flight conditions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.12C
• /
• pp.1082-1087
• /
• 2008

Maximum Likelihood (ML) detection is well known to exhibit better bit-error-rate (BER) than many other detectors for multiple-input multiple-output (MIMO) channel. However, ML detection has been shown a difficult problem due to its NP-hard problem. It means that there is no known algorithm which can find the optimal solution in polynomial-time. In this paper, Semi-Definite relaxation (SDR) is iteratively applied to ML detection problem. The probability distribution can be obtained by survival eigenvector out of the dominant eigenvalue term of the optimal solution. The probability distribution which is yielded by SDR is recurred to the received signal. Our approach can reach to nearly ML performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.221-227
• /
• 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 Electrical Engineering and Technology
• /
• v.4 no.4
• /
• pp.457-466
• /
• 2009

This paper presents efficient parallel genetic algorithm (EPGA) based decomposed network for optimal power flow with various kinds of objective functions such as those including prohibited zones, multiple fuels, and multiple areas. Two coordinated sub problems are proposed: the first sub problem is an active power dispatch (APD) based parallel GA; a global database generated containing the best partitioned network: the second subproblem is an optimal setting of control variables such as generators voltages, tap position of tap changing transformers, and the dynamic reactive power of SVC Controllers installed at a critical buses. The proposed approach tested on IEEE 6-bus, IEEE 30-bus and to 15 generating units and compared with global optimization methods (GA, DE, FGA, PSO, MDE, ICA-PSO). The results show that the proposed approach can converge to the near solution and obtain a competitive solution with a reasonable time.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.1213-1216
• /
• 2005

In this paper, we suggested the integer linear programming (ILP) models that went through constraint scheduling to simple cycle operation during the delay time. The delayed scheduling can determine a schedule with a near-optimal number of control steps for given fixed hardware constraints. In this paper, the resource-constrained problem is addressed, for the DFG optimization for multiprocessor design problem, formulating ILP solution available to provide optimal solution. The results show that the scheduling method is able to find good quality schedules in reasonable time.

• Journal of Korean Institute of Industrial Engineers
• /
• v.26 no.2
• /
• pp.155-164
• /
• 2000

Recently Fiber-optic Micro-cellular Wireless Network is considered to solve frequent handoffs and local traffic unbalance in microcellular systems. In this system, central station which is connected to several microcells by optical fiber manages the channels. We propose an efficient sectorization algorithm which dynamically clusters the microcells to minimize the blocked and handoff calls and to balance the traffic loads in each cell. The problem is formulated as an integer linear programming. The objective is to minimize the blocked and handoff calls. To solve this real time sectorization problem the Tabu Search is considered. In the tabu search intensification by Swap and Delete-then-Add (DTA) moves is implemented by short-term memory embodied by two tabu lists. Diversification is considered to investigate proper microcells to change their sectors. Computational results show that the proposed algorithm is highly effective. The solution is almost near the optimal solution and the computation time of the search is considerably reduced compared to the optimal procedure.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.936-943
• /
• 2002

The Simulated Annealing (SA) algorithm has been successfully applied to various difficult combinatorial optimization problems. Since the performance of a SA algorithm, generally depends on values of the parameters, it is important to select the most appropriate parameter values. In this paper the SA algorithm is optimally designed for performance acceleration, by using the Taguchi method. Several test problems are solved via the SA algorithm optimally designed, and the solutions obtained are compared to solution results McMullen & Frazier(2000). The performance of the SA algorithm is evaluated in terms of solution quality and computation times. Computational results show that the proposed SA algorithm is effective and efficient in finding near-optimal solutions.

• Proceedings of the KIEE Conference
• /
• 2003.07a
• /
• pp.403-405
• /
• 2003

In this paper, we applied a chaos search method for feeder reconfiguration problem in unbalanced distribution system. Chaos method, in optimization problem, searches the global optimal solution on the regularity of chaotic motions and more easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos search method applied to the IEEE 13 unbalanced test feeder systems, and the test results indicate that it is able to determine appropriate switching options for global optimum configuration.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.164-175
• /
• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.