• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.344-347
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• 2011

In this paper, we propose the power control problem for cognitive radio networks (CRNs) that maximizes the total utility of the secondary users (SUs). We use the interference temperature constraints to protect the primary users (PUs). The utility functions of SUs can be any increasing functions. We formulate the power control problem as monotonic optimization that can be solved in centralization to achieve the global optimum.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.651-652
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• 2008

In this paper, we suggest a new multiobjective optimization algorithm which is based on the simulated annealing(SA) method. The proposed algorithm uses population-based simulated annealing and adapts elitism in the process of selection.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1332-1339
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• 1989

The problem of finding an admissible object trajectory for a cooperating two-robot system is investigated. The method is based on reformulating the problem as a nonlinear optimization problem with equality constraints in terms of the joint variables. The optimization problem is then solved numerically on a computer. The solution automatically gives the corresponding joint variable trajectories as well, thus eliminating the need for solving the inverse kinematic problem. The performance indices are chose in joint and cartesian spaces and computer simulations are performed.

• Journal of the Optical Society of Korea
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• v.11 no.2
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• pp.55-58
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• 2007

We propose a systematic method for design of fiber-optic surface plasmon resonance (SPR) sensors. We used rigorous coupled wave analysis (RCWA) for analysis of the transmission spectrum, and the (1+1) evolution strategy (ES) was employed as an optimization tool. The simulation results show that the optimization method presented here is very useful in designing fiber-optic SPR sensor for strain and temperature measurement. This algorithm can be extended to another objective function with other weighting factors and optical parameters.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.157-164
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• 2022

The proposed privacy preserving scheme has identified the drawbacks of existing schemes in Vehicular Networks. This prototype enhances the number of nodes by decreasing the cluster size. This algorithm is integrated with the whale optimization algorithm and Block Chain Technology. A set of results are done through the NS-2 simulator in the direction to check the effectiveness of proposed algorithm. The proposed method shows better results than with the existing techniques in terms of Delay, Drop, Delivery ratio, Overhead, throughout under the denial of attack.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.590-600
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• 2008

This paper concerns the development of a designer friendly hull form parameterization and its coupling with advanced global optimization algorithms. As optimization algorithms, we choose the Partial Swarm Optimization(PSO) recently introduced to solve global optimization problems. Most general-purpose optimization softwares used in industrial applications use gradient-based algorithms, mainly due to their convergence properties and computational efficiency when a relatively few number of variables are considered. However, local optimizers have difficulties with local minima and non-connected feasible regions. Because of the increase of computer power and of the development of efficient Global Optimization (GO) methods, in recent years nongradient-based algorithms have attracted much attention. Furthermore, GO methods provide several advantages over local approaches. In the paper, the derivative-based SQP and the GO approach PSO are compared with their relative performances in solving some typical ship design optimization problem focusing on their effectiveness and efficiency.

• International Journal of Fluid Machinery and Systems
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• v.8 no.3
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• pp.209-219
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• 2015

A robust multi-fidelity optimization methodology has been developed, focusing on efficiently handling industrial runner design of hydraulic Francis turbines. The computational task is split between low- and high-fidelity phases in order to properly balance the CFD cost and required accuracy in different design stages. In the low-fidelity phase, a physics-based surrogate optimization loop manages a large number of iterative optimization evaluations. Two derivative-free optimization methods use an inviscid flow solver as a physics-based surrogate to obtain the main characteristics of a good design in a relatively fast iterative process. The case study of a runner design for a low-head Francis turbine indicates advantages of integrating two derivative-free optimization algorithms with different local- and global search capabilities.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.412-417
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• 2008

In a traditional topology optimization method, material properties are usually distributed by finite element density and visualized by a gray level image. The distribution method based on element density is adequate for a great mass of 2-D topology optimization problems. However, when it is used for 3-D topology optimization, it is always difficult to obtain a smooth model representation, and easily appears a virtualconnect phenomenon especially in a low-density domain. The 3-D structural topology optimization method has been developed using the node density instead of the element density that is based on SIMP (solid isotropic microstructure with penalization) algorithm. A computer code based on Matlab was written to validate the proposed method. When it was compared to the element density as design variable, this method could get a more uniform density distribution. To show the usefulness of this method, several typical examples of structure topology optimization are presented.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• Journal of Magnetics
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• v.18 no.3
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• pp.283-288
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• 2013

This paper presents structural topology optimization that is being applied for the design of electromagnetic vibration energy harvester. The design goal is to maximize the root-mean-square value of output voltage generated by external vibration leading structures. To calculate the output voltage, the magnetic field analysis is performed by using the finite element method, and the obtained magnetic flux linkage is interpolated by using Lagrange polynomials. To achieve the design goal, permanent magnet is designed by using topology optimization. The analytical design sensitivity is derived from the adjoint variable method, and the formulated optimization problem is solved through the method of moving asymptotes (MMA). As optimization results, the optimal location and shape of the permanent magnet are provided when the magnetization direction is fixed. In addition, the optimization results including the design of magnetization direction are provided.