• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.491-494
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• 2013

This paper proposes a stochastic/dynamic routing protocol which aims the minimization of the summation of time average expected power expenditure with buffer stability in mobile ad-hoc 60 GHz wireless networks. By using 60 GHz RF, the wireless devices can transmit/receive 1080p HD video signals without compression. In addition, our algorithm works without centralized controller, so that the distributed operation is available. The novelty of the proposed algorithm was also verified by simulations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.21-26
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• 2003

The well-conditioned observer in a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic issues such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic issues such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_2$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic issues and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Journal of the Korea Society for Simulation
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• v.9 no.1
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• pp.93-108
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• 2000

The stochastic manufacturing system has one or more random variables as inputs that lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of the system. These estimates could greatly differ from the corresponding real characteristics for the system. Multiple replications are necessary to get reliable information on the system and output data should be analyzed to get optimal solution. It requires too much computation time practically, In this paper a GA method, named Stochastic Genetic Algorithm(SGA) is proposed and tested to find the optimal solution fast and efficiently by reducing the number of replications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.1-9
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• 2012

Decisions on reliability screening rules and burn-in policies are determined based on the estimated reliability. The variability in a semiconductor manufacturing process does not only causes quality problems but it also makes reliability estimation more complicated. This study investigates the nonuniformity characteristics of integrated circuit reliability according to defect density distribution within a wafer and between wafers then develops optimal burn-in policy based on the estimated reliability. New reliability estimation model based on yield information is developed using a spatial stochastic process. Spatial defect density variation is reflected in the reliability estimation, and the defect densities of each die location are considered as input variables of the burn-in optimization. Reliability screening and optimal burn-in policy subject to the burn-in cost minimization is examined, and numerical experiments are conducted.

• Journal of Industrial Technology
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• v.23 no.A
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• pp.15-20
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• 2003

Stochastic simulation technique has advantages over deterministic simulation in various engineering analysis, since stochastic simulation can take into consideration of scattering of various design variables, which is inherent characteristics of physical world. In this work, Monte-Carlo simulation mothod in ADAMS/Insight for steady-state cornering and J-turn behavior of a truck with design variables like hard points and busing stiffnesses have performed to achieve better dynamic performance. The main purpose is to improve understeer gradient at steady-state cornering and minimize peak lateral acceleration and peak yaw rate at J-turn. Through correlation analysis, design variables that have high impacts on the cornering behavior were selected, and significant performance improvement has been achieved by appropriately changing the high impact design variables.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.75-80
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• 1999

This paper presents a new method to find a optimal solution for stochastic system. This method uses Genetic Algorithm(GA) and simulation. GA is used to search for new alternative and simulation is used to evaluate alternative. The stochastic system has one or more random variables as inputs. Random inputs lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of they system. These estimates could greatly differ from the corresponding real characteristics for the system. We need multiple replications to get reliable information on the system. And we have to analyze output data to get a optimal solution. It requires too much computation to be practical. We address the problem of reducing computation. The procedure on this paper use GA character, an iterative process, to reduce the number of replications. The same chromosomes could exit in post and present generation. Computation can be reduced by using the information of the same chromosomes which exist in post and present current generation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.6
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• pp.49-55
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• 2004

The increase of computing power makes stochastic optimization algorithms available in structural design. One of the stochastic algorithms, simulated annealing algorithm, has been applied to various structural optimization problems. By applying several cooling schedules such as simulated annealing (SA), Boltzmann annealing (BA), fast annealing (FA) and adaptive simulated annealing (ASA), truss structures are optimized to improve the quality of objective functions and reduce the number of function evaluations. In this paper, many cooling parameters have been applied to the cooling schedule of ASA. The influence of cooling parameters is investigated to find the rules of thumb for using ASA. Tn addition, the cooling schedule combined with BA and ASA is applied to the optimization of ten bar-truss and twenty five bar-truss structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.118-124
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• 2015

The design of radar absorbing structures(RAS) is a discrete optimization problem and is usually processed by stochastic optimization methods. The calculation of radar cross section(RCS) should be decreased to improve the efficiency of designing RAS. In this paper, an efficient method using impedance matching is studied to design RAS for minimizing RCS. Input impedance of the minimal RCS for the specified wave incident conditions is obtained by interlocking physical optics(PO) and optimizations. Complex permittivity and thickness of RAS are designed to satisfy the calculated input impedance by a discrete optimization. The results reveal that the studied method attains the same results as stochastic optimization which have to conduct numerous RCS analysis. The efficiency of designing RAS can be enhanced by reducing the calculation of RCS.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.115-125
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• 2021

Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the "curse of dimensionality" when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.