• Kyungpook Mathematical Journal
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• v.31 no.2
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• pp.143-150
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• 1991

• Journal of the Korean Regional Science Association
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• v.8 no.1
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• pp.87-98
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• 1992

• IE interfaces
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• v.13 no.3
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• pp.539-547
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• 2000

An architecture of a Web-based Decision Support system for mathematical analysis is presented. Front-end modules provide web-client GUI environment for mathematical analysis. The networking architecture is built upon client/server system by Java socket and accesses database by JDBC in WWW. Back-end modules provide decision supporting service and data management for mathematical programming analysis. In the back-end any analysis tools, such as mathematical optimizer, simulation package, or statistics package can be used. As an application example for this implementation, optimal facility replacement decision problem is selected. In the implementation the optimal facility replacement decision problem is formulated as a shortest path problem. It uses Oracle DB and CPLEX package as the mathematical optimizer. While ORAWeb is designed and implemented on the optimal facility replacement problem, it can easily be extended to any decision supporting problems that would require mathematical optimization process.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1243-1252
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• 2005

A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.93-102
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• 2007

The frontal crash optimization of an engine room member using the response surface method was studied. The engine room member is composed of the front side member and the sub-frame. The thicknesses of the panels on the front side member and the sub-frame were selected as the design variables. The purpose of the optimization was to reduce the weight of the structure, under the constraint that the objective quantity of crash energy is absorbed. The response surface method was used to approximate the crash behavior in mathematical form for optimization procedure. To research the effect of the regression method, two different methodologies were used in constructing the response surface model, the least square method and the moving least square method. The optimum with the two methods was verified by the simulation result. The precision of the surrogate model affected the optimal design. The moving least square method showed better approximation than the least square method. In addition to the deterministic optimization, the reliability-based design optimization using the response surface method was executed to examine the effect of uncertainties in design variables. The requirement for reliability made the optimal structure be heavier than the result of the deterministic optimization. Compared with the deterministic optimum, the optimal design using the reliability-based design optimization showed higher crash energy absorption and little probability of failure in achieving the objective.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1782-1791
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• 2017

In this paper, an optimal design of hybrid magnetic levitation(Maglev) system using intelligent optimization algorithms is proposed. The proposed maglev system adopts hybrid suspension system with permanent-magnet(PM) and electro magnet(EM) to reduce the suspension power loss and the teaching-learning based optimization(TLBO) that can overcome the drawbacks of conventional intelligent optimization algorithm is used. To obtain the mathematical model of hybrid suspension system, the magnetic equivalent circuit including leakage fluxes are used. Also, design restrictions such as cross section areas of PM and EM, the maximum length of PM, magnetic force are considered to choose the optimal parameters by intelligent optimization algorithm. To meet desired suspension power and lower power loss, the multi object function is proposed. To verify the proposed object function and intelligent optimization algorithms, we analyze the performance using the mean value and standard error of 10 simulation results. The simulation results show that the proposed method is more effective than conventional optimization methods.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.5
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• pp.245-249
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• 2006

This study tries to test and analyze the static friction torque generated by an electromagnetic clutch. Then the torque is improved by optimizing the shape of armature. For the purpose of design change and optimization of the electromagnetic clutch, the static friction torque prediction is very important. We construct an axi symmetric FEM model for analyzing the static friction torque and used a torque tester for evaluating the real torque. For a test, predicted static friction torque is compared with the experimental one to discuss the rationality of torque analysis process. The analytical result agrees well with experimental data, explaining the validity of the mathematical process and FEM model. After confirming the torque analysis process, the optimization process is investigated. The optimization result shows that the static torque is improved by changing the armature shape.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.7-11
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• 2015

The luffing-tower crane (T/C) is a key facility used in the vertical and horizontal transportation of materials in a tall building construction. Locating the crane in an optimal position is an essential task in the initial stages of construction planning. This paper proposes a new optimization model to locate the luffing T/C in the optimal position to minimize the transportation time. A newly developed mathematical formula is suggested to calculate the transportation time of luffing T/C correctly. An optimization algorithm, the Harmony Search (HS) algorithm, was used and the results show that HS has high performance characteristics to solve the optimization problem in a short period of time. In a case study, the proposed model offered a better position for T/C than the previous heuristic approach.

• Structural Engineering and Mechanics
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• v.13 no.5
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• pp.479-490
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• 2002

The structural dynamic optimization problem based on probability is studied. Considering the randomness of structural physical parameters and the given constraint values, we develop a dynamic optimization mathematical model of engineering structures with the probability constraints of frequency, forbidden frequency domain and the vibration mode. The sensitivity of structural dynamic characteristics based on probability is derived. Two examples illustrate that the optimization model and the method applied are rational and efficient.