• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.224-226
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• 1997

This paper describes a procedure for the optimal design of induction motor for electric vehicle. The immune algorithm is applicated for the optimal solution search. To verify the validity of the proposed method, a example disign for output 20[kw] is performed.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.84-92
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• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• Structural Engineering and Mechanics
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• v.92 no.1
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• pp.99-110
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• 2024

The crack propagation path can be considered as a boundary problem in which the crack advances towards the interior of the domain. Consequently, this poses an optimization problem wherein the local crack-growth direction angle can be treated as a design variable. The advantage of this approach is that the continuous minimization of strain energy naturally leads to the mode I propagation path. Furthermore, this procedure does not rely on the precise characterization of the stress field at the crack tip and is independent of stress intensity factors. This paper proposes an algorithm based on internal point exploration as well as shape sensitivity optimization and strain energy minimization to determine the crack propagation direction. To implement this methodology, the algorithm utilizes a modeling GUI associated with an academic analysis program based on the Dual Boundary Elements Method and determines the propagation path by exploiting the elastic strain energy at points in the domain that are candidates to be included in the boundary. The sensitivity of the optimal solution is also assessed in the vicinity of the optimum point, ensuring the stability and robustness of the solution. The results obtained demonstrate that the proposed methodology accurately predicts the crack propagation direction in Mode I opening for a single crack (lateral and central). Furthermore, robust optimal solutions were achieved in all cases, indicating that the optimal solution was not highly sensitive to changes in the design variable in the vicinity of the optimal point.

• Korean Management Science Review
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• v.15 no.1
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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.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.852-854
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• 2005

This paper proposes a new Interior Point Method algorithm to improve the computation speed and solution stability, which have been challenging problems for employing the nonlinear Optimal Power Flow. The proposed algorithm is different from the traditional Interior Point Methods in that it adopts the Predictor-Corrector Method. It also accommodates the five minute dispatch, which is highly recommended in modern electricity market. Finally, the efficiency and applicability of the proposed algorithm is demonstrated with a case study.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.75-85
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• 1983

This study is concerned with the problem of routing vehicles stationed at a central depot to supply customers with known demands, in such a way as to minimize the total distance travelled. The problem is referred to as the vehicle routing problem and is a generalization of the multiple traveling salesmen problem that has many practical applications. A branch-and-bound algorithm for the exact solution of the vehicle routing problem is presented. The algorithm finds the optimal number of vehicles as well as the minimum distance routes. A numerical example is given.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.235-245
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• 2008

The purpose of this paper is to develop a genetic algorithm to determine the optimal locations of base stations and relay stations in Wibro MMR Network. Various issues related to the genetic algorithm such as solution representation, selection method, crossover operator, mutation operator, and a heuristic method for improving the quality of solutions are presented. The computational results are presented for determining optimal parameters for the genetic algorithm, and show the convergence of the genetic algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.866-870
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• 2010

This paper presents a application of Harmony Search (HS) algorithm for optimal placement of distributed generations(DGs) in distribution systems. In optimization procedure, the HS algorithm denotes the searching ability for the global optimal solution with simple coding of the iteration procedure, and shows the fast convergence characteristics for getting solutions. The HS algorithm is tested on 9 buses and 69 buses distribution systems, and the results prove its effectiveness to determine appropriate placement points of DGs and reducing amount of active power without the occurrence of any mis-determination in selection of its capacity.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.869-874
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• 2007

In searching for solutions to multiobjective optimization problem, we find that there is no single optimal solution but rather a set of solutions known as 'Pareto optimal set'. To find approximation of ideal pareto optimal set, search capability of diverse individuals at population space can determine the performance of evolutionary algorithms. This paper propose the method to maintain population diversify and to find non-dominated alternatives in Game model based Co-Evolutionary Algorithm.