• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Steel and Composite Structures
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• v.19 no.2
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• pp.503-519
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• 2015

This paper presents an optimization process using Genetic Algorithm (GA) for minimum weight by selecting suitable standard sections from a specified list taken from American Institute of Steel Construction (AISC). The stress constraints obeying AISC-LRFD (American Institute of Steel Construction-Load and Resistance Factor Design), lateral displacement constraints being the top and inter-storey drift, mid-span deflection constraints for the beams and geometric constraints are considered for optimum design by using GA that mimics biological processes. Optimum designs for three different space frames taken from the literature are carried out first without considering concrete slab effects in finite element analyses for the constraints above and the results are compared with the ones available in literature. The same optimization procedures are then repeated for the case of space frames with composite (steel and concrete) beams. A program is coded in MATLAB for the optimization processes. Results obtained in the study showed that consideration of the contribution of the concrete on the behavior of the floor beams results with less steel weight and ends up with more economical designs.

• Steel and Composite Structures
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• v.33 no.6
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• pp.767-776
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• 2019

In this article, a simple and robust multi-objective assessment method to control design angles and node positions connected among steel outrigger truss members is proposed to approve both structural safety and economical cost. For given outrigger member layouts, the present method utilizes general-purpose prototypes of outrigger members, having resistance to withstand lateral load effects directly applied to tall buildings, which conform to variable connecting node and design space deposition. Outrigger layouts are set into several initial design conditions of height to width of an arbitrary given design space, i.e., variable design space. And then they are assessed in terms of a proposed multi-objective function optimizing both minimal total displacement and material quantity subjected to design impact factor indicating the importance of objectives. To evaluate the proposed multi-objective function, an analysis model uses a modified Maxwell-Mohr method, and an optimization model is defined by a ground structure assuming arbitrary discrete straight members. It provides a new robust assessment model from a local design point of view, as it may produce specific optimal prototypes of outrigger layouts corresponding to arbitrary height and width ratio of design space. Numerical examples verify the validity and robustness of the present assessment method for controlling prototypes of outrigger truss members considering a multi-objective optimization achieving structural safety and material cost.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.04a
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• pp.102-109
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• 1999

Two phase simulated annealing algorithm is presented as a structural optimization technique and applied to minimum weight design of space trusses subjected to stress and displacement constraints under multiple loading conditions. Univariate searching algorithm is adopted for automatic selection of initial values of design variables for SA algorithm. The proper values of cooling factors and reasonable stopping criteria for optimum design of space truss structures are proposed to enhance the performance of optimization process. Optimum weights and design solutions are presented for two well-blown example structures and compared with those reported in the literature.

• Journal of Korean Association for Spatial Structures
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• v.3 no.4 s.10
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• pp.59-67
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• 2003

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. Genetic algorithm tends to thrive in an environment in which the search space is uneven and has many hills and valleys. In this study, genetic algorithm is used for solving the design problem of gable structure. The design problem of frame structure has some special features(complicate design space, many nonlinear constrants, integer design variables, termination conditions, special information for frame members, etc.), and these features must be considered in the formulation of optimization problem and the application of genetic algorithm. So, 'FRAME operator', a new genetic operator for solving the frame optimization problem effectively, is developed and applied to the design problem of gable structure. This example shows that the new opreator has the possibility to be an effective frame design operator and genetic algorithm is suitable for the frame optimization problem.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.1-12
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• 2019

This study investigates optimum designs of steel space truss towers under seismic loading by using Jaya optimization algorithm. Turkish Earthquake Code (2007) specifications are applied on optimum designs of steel space truss towers under the seismic loading for different local site classes depending on different soil groups. The proposed novel algorithm does not have any algorithm-specific control parameters and depends only a simple revision equation. Therefore, it provides a practical solution for structural optimization problems. Optimum solutions of the different steel truss examples are carried out by selecting suitable W sections taken from American Institute of Steel Construction (AISC). In order to obtain optimum solutions, a computer program is coded in MATLAB in corporated with SAP2000-OAPI (Open Application Programming Interface). The stress and displacement constraints are applied on the design problems according to AISC-ASD (Allowable Stress Design) specifications. Firstly, a benchmark truss problem is examined to see the efficiency of Jaya optimization algorithm. Then, two different multi-element truss towers previously solved with other methods without seismic loading in literature are designed by the proposed algorithm. The first space tower is a 582-member space truss with the height of 80 m and the second space tower is a 942-member space truss of about 95 m height. The minimum optimum designs obtained with this novel algorithm for the case without seismic loading are lighter than the ones previously attained in the literature studies. The results obtained in the study show that Jaya algorithm is a practical and robust optimization method for structural optimization problems. Moreover, incorporation of the seismic loading causes significant increase in the minimum design weight.

• Journal of Korean Association for Spatial Structures
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• v.1 no.2 s.2
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• pp.59-66
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• 2001

This paper describes three modules for development of the Space Frame Integrated Design System(SFIDS). The Control Module is implemented to control the developed system. The Model Generation Module based on PATRAN user interface enables users to generate a complicated finite element model for space frame structures. The Optimum Design Module base on a branch of combinatorial optimization techniques which can realize the optimization of a structure having a large number of members designs optimum members of a space frame after evaluating analysis results. The Control Module and the Model Generation Module Is implemented by PATRAN Command Language(PCL) while C++ language is used in the Optimum Design Module. The core of the system is PATRAN database, in which the Model Generation Module creates information of a finite element model. Then, PATRAN creates Input files needed for the analysis program from the information of the finite element model in the database, and in turn, imports output results of analysis program to the database. Finally, the Optimum Design Module processes member grouping of a space frame based on the output results, and performs optimal member selection of a space frame. This process is repeated until the desired optimum structural members are obtained.

• International Journal of Automotive Technology
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• v.6 no.6
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• pp.635-641
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• 2005

This paper presents an ASF (Aluminum Space Frame) BIW (Body in White) optimal design, which minimizes weight and satisfies multidisciplinary constraints such as static stiffness, vibration characteristics, low-/high-speed crash, and occupant safety. As only one cycle CPU time for all the analyses is 12 hours, the ASF design having 11-design variable is a large scaled problem. In this study, ISCD-II and conservative least square fitting method were used for efficient RSM modeling. Likewise, the ALM method was used to solve the approximate optimization problem. The approximate optimum was sequentially added to remodel the RSM. The proposed optimization method uses only 20 analyses to solve the 11-design variable problem. Moreover, the optimal design can achieve $15.6\%$ weight reduction while satisfying all the multidisciplinary design constraints.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.1-10
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• 2005

A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.12
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• pp.1121-1128
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• 2007

MDO(Multidisciplinary Design and Optimization) can be applied for design of complex systems such as aircraft and SLV(Space Launch Vehicle). MDO System can be an integrated environment or a system, which is for synthetic and instantaneous analysis and design optimization in various design fields. MDO System has to efficiently use and integrate distributed resources such as various analysis codes, optimization codes, CAD, DBMS, GUI, and etc. in heterogeneous environments. In this paper, we present Web Services-based MDO System that integrates resources for MDO using Globus Toolkit and provides organic autonomous execution using automation technique such as Workflow system and agent. And also, it provides collaborative design environment through web user interfaces.