• Elastomers and Composites
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• v.34 no.4
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• pp.321-331
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• 1999

The curing process is the final step in tire manufacturing whereby a green tire built from layers of rubber compounds is formed to the desired shape and the compounds are converted to a strong, elastic materials to meet tire performance needs under elevated pressure and temperature in a press. A numerical optimization procedure was developed to improve product quality in a tire curing process. First, a dynamic constrained optimization problem was formulated to determine the optimal condition of the supplied cure media during a curing process. The objective function is subject to an equality constraint representing the process model that describes the heat transfer and cures kinetic phenomena in a cure press and is subject to inequality constraints representing temperature limits imposed on cure media. Then, the optimization problem was solved to determine optimal condition of the supplied cure media for a tire using the complex algorithm along with a finite element model solver.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.56-63
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• 2015

The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.857-862
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• 2004

This paper analyzes properties of the recently developed nonlinear optimization method, Dynamic Encoding Algorithm for Searches (DEAS) [1]. DEAS locates local minima with binary strings (or binary matrices for multi-dimensional problems) by iterating the two operators; bisectional search (BSS) and unidirectional search (UDS). BSS increases binary strings by one digit (i.e., zero or one), while UDS performs increment or decrement to binary strings with no change of string length. Owing to these search routines, DEAS retains the optimization capability that combines the special features of several conventional optimization methods. In this paper, a special feature of BSS and UDS in DEAS is analyzed. In addition, a effective global search strategy is established by using information of DEAS. Effectiveness of the proposed global search strategy is validated through the well-known benchmark functions.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.691-700
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• 2007

This paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang#s and Ho#s methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.544-556
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• 1991

The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust and efficient. A general-purpose nonlinear optimization program IDOL (Interactive Design Optimization Library) is developed based on the Augmented Lagrange Mulitiplier (ALM) method. The ideas of selecting a good initial design point, using resonable initial values for Lagrange multipliers, constraints scaling, descent vector restarting, and dynamic stopping criterion are employed for computational enhancement to the ALM method. A descent vector is determined by using the Broydon-Fletcher-Goldfarb-Shanno (BFGS) method. For line search, the Incremental-Search method is first used to find bounds on the solution, then the bounds are reduced by the Golden Section method, and finally a cubic polynomial approximation technique is applied to locate the next design point. Seven typical test problems are solved to show IDOL efficient and robust.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.120-123
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• 2005

A dynamic system identification technique based on the topology optimization method is developed. The specific problem in consideration is the damage location identification of a plate structure using the Frequency Response Function (FRF) of a damaged structure. In this work, the identification problem is formulated as a topology optimization problem. The importance of using anti-resonance information in addition to using resonance information is addressed. Though a simple problem was considered here, the possibility of using the topology optimization for damage identification is investigated lot the first time.

• Journal of KSNVE
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• v.10 no.3
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• pp.437-443
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• 2000

The optimal design problem for increasing dynamic stiffness using hybrid model which composed of original detailed BIW(body in white) and impinged beam elements is investigated. Using the characteristics of the beam elements and design sensitivity analysis this approach utilizes an optimization technique to determine the optimal section properties of beam elements. The constraint is to increase the first natural frequency by five percent compared with original one. The results show that the first torsion and bending natural frequencies are increased by five percent using hybrid model and optimization. These results indicate that this optimization method can be employed to enhance the dynamic stiffness of vehicle body structure in design concept stage.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.263-270
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• 2002

This study proposes a multi-objective optimum design method for a rational optimization of high-speed railway bridges. This multi-objective optimization is found to be effective in optimizing multi-objective problems that incorporate cost and dynamic responses such as vertical acceleration and displacement. These design factors are so important in the high-speed railway bridges. And the trade off method which is one of the most typical multi-objective optimization methods is used in this study, since the dynamic factors are formulated as objective function and also considered as constraints. And the Pareto curve can be obtained by performing the multi-objective optimization for real high-speed railway bridges. Thus, it is found that more reasonable design can be obtained when compared with those using conventional design procedure.

• Journal of the korean Society of Automotive Engineers
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• v.15 no.1
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• pp.81-88
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• 1993

A direct treatment of the min-max type objective function of the dynamic response optimization problem is proposed. Previously, the min-max type objective function was transformed to an artificial design variable and an additional point-wise state variable constraint function was imposed, which increased the complexity of the optimization problem. Especially, the design sensitivity analysis for the augmented Lagrangian functional with the suggested treatment is established by using the adjoint variable method and a computer program to implement the proposed algorithm is developed. The optimization result of the proposed treatment are obtained for three typical problems and compared with those of the previous treatment. It is concluded that the suggested treatment in much more efficient in the computational effort than the previous treatment with giving the similar optimal solutions.

• Steel and Composite Structures
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• v.44 no.2
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• pp.211-224
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• 2022

Multi-objective optimization was conducted to obtain the optimal configuration of a composite sandwich structure with honeycomb-foam hybrid core subjected to underwater shock waves, which can fulfill the demand for light weight and energy efficient design of structures against underwater blast. Effects of structural parameters on the dynamic response of the sandwich structures subjected to underwater shock waves were analyzed numerically, from which the correlations of different parameters to the dynamic response were determined. Multi-objective optimization of the structure subjected to underwater shock waves of which the initial pressure is 30 MPa was conducted based on surrogate modelling method and genetic algorithm. Moreover, optimization results of the sandwich structure subjected to underwater shock waves with different initial pressures were compared. The research can guide the optimal design of composite sandwich structures subjected to underwater shock waves.