• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1994년도 추계학술발표회 및 정기총회
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.

• Steel and Composite Structures
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• 제21권1호
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• pp.217-247
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• 2016

Five extended cylindrical reticulated shells are proposed by changing distribution rule of diagonal rods based on three fundamental types. Modeling programs for fundamental types and extended types of cylindrical reticulated shell are compiled by using the ANSYS Parametric Design Language (APDL). On this basis, conditional formulas are derived when the grid shape of cylindrical reticulated shells is equilateral triangle. Internal force analysis of cylindrical reticulated shells is carried out. The variation and distribution regularities of maximum displacement and stress are studied. A shape optimization program is proposed by adopting the sequence two-stage algorithm (RDQA) in FORTRAN environment based on the characteristics of cylindrical reticulated shells and the ideas of discrete variable optimization design. Shape optimization is achieved by considering the objective function of the minimum total steel consumption, global and locality constraints. The shape optimization for three fundamental types and five extended types is calculated with the span of 30 m~80 m and rise-span ratio of 1/7~1/3. The variations of the total steel consumption along with the span and rise-span ratio are analyzed with contrast to the results of shape optimization. The optimal combination of main design parameters for five extended cylindrical reticulated shells is investigated. The total steel consumption affected by distribution rule of diagonal rods is discussed. The results show that: (1) Parametric modeling method is simple, efficient and practical, which can quickly generate different types of cylindrical reticulated shells. (2) The mechanical properties of five extended cylindrical reticulated shells are better than their fundamental types. (3) The total steel consumption of cylindrical reticulated shells is optimized to be the least when rise-span ratio is 1/6. (4) The extended type of three-way grid cylindrical reticulated shell should be preferentially adopted in practical engineering. (5) The grid shape of reticulated shells should be designed to equilateral triangle as much as possible because of its reasonable stress and the lowest total steel consumption.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.881-882
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• 2013

• Advances in materials Research
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• 제1권2호
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• pp.129-146
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• 2012

Polycrystalline diamond is an ideal material for parts with micro-holes and has been widely used as dies and cutting tools in automotive, aerospace and woodworking industries due to its superior wear and corrosion resistance. In this research paper, the modeling and simultaneous optimization of multiple performance characteristics such as material removal rate and surface roughness of polycrystalline diamond (PCD) with ultrasonic machining process has been presented. The fuzzy logic and taguchi's quality loss function has been used. In recent years, fuzzy logic has been used in manufacturing engineering for modeling and monitoring. Also the effect of controllable machining parameters like type of abrasive slurry, their size and concentration, nature of tool material and the power rating of the machine has been determined by applying the single objective and multi-objective optimization techniques. The analysis of results has been done using the MATLAB 7.5 software and results obtained are validated by conducting the confirmation experiments. The results show the considerable improvement in S/N ratio as compared to initial cutting conditions. The surface roughness of machined surface has been measured by using the Perthometer (M4Pi, Mahr Germany).

• 한국항공우주학회지
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• 제37권1호
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• pp.42-54
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• 2009

비행체의 최적궤적문제에서는 최적화의 수렴성 및 효율성을 위해 3자유도 운동역학모델이 이용되며, 비선형 추종제어를 위해서는 6자유도 비선형 운동모델이 이용된다. 따라서, 3자유도 운동역학모델을 통해 획득한 최적궤적을 비선형 추종제어의 기준궤적으로 사용하는 경우에 두 모델간의 상이성으로 인한 문제가 발생하게 되며 성능이 보장하지 못한다. 본 논문에서는 이러한 두 모델간의 차이를 완화시키기 위한 새로운 최적궤적 생성 방법을 제안하였으며, 성층권비행선의 실제 구속조건과 성능조건 및 제트 스트림을 고려하여 최적궤적을 생성하고 기존 결과와 비교함으로써 제안한 방법의 장점을 검증하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

• Smart Structures and Systems
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• 제26권4호
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• Earthquakes and Structures
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• 제7권3호
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• pp.271-294
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• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1057-1062
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• 2008

Representing a complex, three-dimensional shape, such as an automobile, requires a large amount of CAD data consisting of millions of approximated discontinuous points, which makes it difficult or even impossible to efficiently optimize the entire shape. For this reason, in this paper, function based design method is proposed to optimize the external shape of an automobile. A vehicle modeling function was defined in the form of a Bernstein polynomial to smoothly express the complex 2D and 3D automobile configurations. The sub-sectional parts of the vehicle modeling function are defined as section functions through classifying each subsection of a box model. It is shown that the use of the vehicle modeling functions has the useful advantages in an aerodynamic shape optimization.

• Computers and Concrete
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• 제14권4호
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• pp.445-462
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• 2014

To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.