• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.105-113
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• 2002

As the number of pedestrian accident increases, the reconstruction of an accident becomes important to find the source of the fault. Generally, accidents are reconstructed by the intuition of experts or primitive physics. A reconstruction method is proposed using sophisticated optimization technology. At first, a dynamic simulation model is established for the accident environment. Occupant analysis for automobile crashworthiness is employed. The situation before an accident is identified by optimization. The impact velocity and the position of the pedestrian are utilized as design variables. The design variables are found by minimizing the difference between the simulation and the real accident. The optimization process is performed by linking an occupant analysis program MADYMO to an optimization program VisualDOC. Since the involved analysis is dynamics and highly nonlinear, response surface method is selected for the optimization process. Problems are solved for various situations.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.53-62
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• 2004

This paper presents a study on the optimization for brokering between cargos and ships for future e-logistics. The primary contribution of this research is that we establish an optimization model by formalizing the criteria for the brokering such as time constraints, weight constraints, and preference values between cargos and ships. Another important contribution is that we not only investigate the complexity and the tractability of the optimal brokering problem but present how to evaluate the performance of the optimization program through an experiment. We first derive the preference values between cargos and ships using the time and the weight constraints. These preference values between each pair of cargos and ships are assigned to corresponding binary decision variables as coefficients in the objective function. The optimization model selects pairs of cargos and ships in a way that the sum of the preference values is maximized while satisfying given constraints. Experiment shows that the Davis-Putnam based optimization program finds optimal solutions in reasonable time for the problems with less than 90 decision variables.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.217-224
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• 2020

In this study, a framework for optimizing the opening in an outrigger wall is proposed. To solve a constrained bounded optimization problem, an in-house finite element program and SQP algorithm in Python SciPy library are utilized. The openings of the outrigger wall are located according to the strut-tie behavior of the outrigger wall deep beam. A linear interpolation method is used to obtain differentiable continuous functions required for optimization, whereas a database is used for the efficiency of the optimization program. By comparing the result of the two-variable optimization through the moving path of the search algorithm, it is confirmed that the algorithm efficiently determines the optimized result. When the size of each opening is set to individual variables rather than the same width of all openings, the value of the objective function is minimized to obtain better optimization results. It was confirmed that the optimization time can be effectively reduced when using the database in the optimization process.

• Steel and Composite Structures
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• v.33 no.5
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• pp.747-753
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• 2019

Metaheuristic algorithm is used to solve the weight minimization problem of truss structures considering shape, and sizing design variables. The cross-sectional areas of the line element in trusses are the design variables for size optimization and the changeable joint coordinates are the shape optimization used in this study. The design of plane and spatial truss structures are optimized by metaheuristic technique named Teaching-Learning-Based Optimization (TLBO). Finite element analyses of structures and optimization process are carried out by the computer program visually developed by the authors coded in MATLAB. The four benchmark problems (trusses 2D ten-bar, 3D thirty-seven-bar, 3D seventy-two-bar and 2D two-hundred-bar) taken from literature are optimized and the optimal solution compared the results given by previous studies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.45-52
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• 2005

A general approximate optimization technique by sequential design domain(SDD) did not save response values for getting an approximate function in each step. It has a disadvantage at aspect of an expense. In this paper, previous response values are recycled for constructing an approximate function. For this reason, approximation function is more accurate. Accordingly, even if we did not determine move limit, a system is converged to the optimal design. Size and shape optimization using approximate optimization technique is carried out with SDD. Algorithm executing Pro/Engineer and ANSYS are automatically adopted in the approximate optimization program by SDD. Convergence criterion is defined such that optimal point must be located within SDD during the three steps. The PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information in the direction finding problem and uses the active set strategy.

• Computers and Concrete
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• v.27 no.2
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• pp.143-152
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• 2021

Large dams are a part of the infrastructure of any society, and a huge amount of resources are consumed to build them. Among the various types of dams, the optimum design of concrete gravity dams requires special attention because these types of dams require a huge amount of concrete for their construction. On the other hand, concrete gravity dams are among the structures whose design, regarding the acting forces, geometric parameters, and resistance and stability criteria, has some complexities. In the present study, an optimization methodology is proposed based on Sequential Quadratic Programming (SQP), and a computer program is developed to perform optimization of concrete gravity dams. The optimum results for 45 concrete gravity dams are studied and regression analyses are performed to obtain some explicit formulas for optimization of the gravity dams. The optimization of concrete gravity dams can be provided easily using the developed formulas, without the need to perform any more optimization process.

• Steel and Composite Structures
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• v.26 no.2
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• pp.163-170
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• 2018

The purpose of this paper is to present a new and efficient optimization algorithm called Jaya for optimum design of steel grillage structure. Constrained size optimization of this type of structure based on the LRFD-AISC is carried out with integer design variables by using cross-sectional area of W-shapes. The objective function of the problem is to find minimum weight of the grillage structure. The maximum stress ratio and the maximum displacement in the inner point of steel grillage structure are taken as the constraint for this optimization problem. To calculate the moment and shear force of the each member and calculate the joint displacement, the finite elements analysis is used. The developed computer program for the analysis and design of grillage structure and the optimization algorithm for Jaya are coded in MATLAB. The results obtained from this study are compared with the previous works for grillage structure. The results show that the Jaya algorithm presented in this study can be effectively used in the optimal design of grillage structures.

• Korean Management Science Review
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• v.15 no.1
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• pp.77-85
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• 1998

In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solutions of a multiple objective linear program. Since the efficient set is in general a nonconvex set, problem (P) can be classified as a global optimization problem. Perhaps due to its inherent difficulty, relatively few attempts have been made to solve problem (P) in spite of the potential benefits which can be obtained by solving problem (P). The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.165-177
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• 2005

In this paper, an adaptive trust region method based on the conic model for unconstrained optimization problems is proposed and analyzed. We establish the global and super linear convergence results of the method. Numerical tests are reported that confirm the efficiency of the new method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.3
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• pp.410-425
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• 1997

Buildings are mostly under part load conditions causing an inefficient system operation in terms of energy consumption. It is critical to operate building air-conditioning system with a scientific or optimal manner which minimizes energy consumption and maintains thermal comfort by matching building sensible and latent loads. Little research has been performed in developing general methodologies for the optimal operation of air-conditioning system. Based on this research motivation, system simulation program was developed by adopting various equipment operating strategies which are energy efficient especially for humidity control in summer. A numerical optimization technique was utilized to search optimal solution for multi-independent variables and then linked to the developed system simulation model within a mam program. The main goal of the study is to provide a systematic framework and guideline for the optimal operation of air-conditioning system focusing on air-side. For given cooling loads and ambient outdoor conditions the optimal operating strategies of a commercial building are determined by minimizing a constrained objective function by a nonlinear programming technique. Desired space setpoint conditions were found through evaluating the trade-offs between comfort and system power consumption. The results show that supply airflow rate and compressor fraction play main roles in the optimization process. It was found that variable setpoint optimization technique could produce lower indoor humidity level demanding less power consumption which will be benefits for building applications of humidity problem.