• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• Earthquakes and Structures
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• 제11권2호
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• Composites Research
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• 제28권5호
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• pp.297-310
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• 2015

This study aims to develop efficient composite laminates for buckling load enhancement, interlaminar shear stress minimization, and weight reduction. This goal is achieved through cover-skin lay-ups around skins and stiffeners, which amplify bending stiffness and defer delamination by means of effective stress distribution. The design problem is formulated as multi-objective optimization that maximizes buckling load capability while minimizing both maximum out-of-plane shear stress and panel weight. For efficient optimization, response surface methodology is employed for buckling load, two out-of-plane shear stresses, and panel weight with respect to one ply thickness, six fiber orientations of a skin, and four stiffener heights. Numerical results show that skin-covered composite stiffened panels can be devised for maximum buckling load and minimum interlaminar shear stresses under compressive load. In addition, the effects of different material properties are investigated and compared. The obtained results reveal that the composite stiffened panel with Kevlar material is the most effective design.

• 한국생산제조학회지
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• 제26권1호
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• pp.30-35
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• 2017

The major parts of a vacuum cleaner are molded. The vacuum cleaner works in multi-load conditions. Therefore, the designer needs to optimize the structure and injection molding conditions simultaneously. Here, the main factor of design is the rib shape and thickness. The greater the rib thickness, the greater the stiffness of the structure. However, it causes an increase in weight. On the other hand, the lower the rib thickness, the greater the increase in the injection pressure. However, the weight will be reduced. Therefore, the designer needs to optimize the rib shape and thickness for structure stiffness and injection molding. In order to solve this problem, we propose an optimization method using D.O.E and a response surface model, which is a multi-objective optimization method using the multi-objective genetic algorithm.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 The Fifth Asian Computational Fluid Dynamics Conference
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• pp.240-242
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• 2003

A method for performing two-dimensional lift-constraint drag minimization in inviscid compressible flows on unstructured meshes is developed. Sensitivities of objective function with respect to the design variables are efficiently obtained by using a continuous adjoint method. In addition, parallel algorithm is used in multi-point design optimization to enhance the computational efficiency. The characteristics of single-point and multi-point optimization are examined, and the comparison of these two method is presented.

• Structural Engineering and Mechanics
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• 제72권2호
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• pp.181-190
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• 2019

Topology optimization of structures seeking the best distribution of mass in a design space to improve the structural performance and reduce the weight of a structure is one of the most comprehensive issues in the field of structural optimization. In addition to structures stiffness as the most common objective function, frequency optimization is of great importance in variety of applications too. In this paper, an efficient multi-objective Bi-directional Evolutionary Structural Optimization (BESO) method is developed for topology optimization of frequency and stiffness in continuum structures simultaneously. A software package including a Matlab code and Abaqus FE solver has been created for the numerical implementation of multi-objective BESO utilizing the weighted function method. At the same time, by considering the weaknesses of the optimized structure in single-objective optimizations for stiffness or frequency problems, slight modifications have been done on the numerical algorithm of developed multi-objective BESO in order to overcome challenges due to artificial localized modes, checker boarding and geometrical symmetry constraint during the progressive iterations of optimization. Numerical results show that the proposed Multiobjective BESO method is efficient and optimal solutions can be obtained for continuum structures based on an existent finite element model of the structures.

• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1080-1086
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• 2005

The preliminary design optimization of multi-stage spur gear reduction units has been a subject of considerable interest, since many high-performance power transmission applications (e.g., automotive and aerospace) require high-performance gear reduction units. There are multiple objectives in the optimal design of multi-stage spur gear reduction unit, such as minimizing the volume and maximizing the surface fatigue life. It is reasonable to formulate the design of spur gear reduction unit as a multi-objective optimization problem, and find an appropriate approach to solve it. In this paper an interactive physical programming approach is developed to place physical programming into an interactive framework in a natural way. Class functions, which are used to represent the designer's preferences on design objectives, are fixed during the interactive physical programming procedure. After a Pareto solution is generated, a preference offset is added into the class function of each objective based on whether the designer would like to improve this objective or sacrifice the objective so as to improve other objectives. The preference offsets are adjusted during the interactive physical programming procedure, and an optimal solution that satisfies the designer's preferences is supposed to be obtained by the end of the procedure. An optimization problem of three-stage spur gear reduction unit is given to illustrate the effectiveness of the proposed approach.

• 전기학회논문지
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• 제62권1호
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.

• 소성∙가공
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• 제30권1호
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• pp.27-34
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• 2021

In this study, response surface method (RSM) was used in modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goals of optimization were the maximum forming angle, minimum thickness reduction, and minimum surface roughness, with varying values in response to changes in production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model for modeling the variations in the forming angle, thickness reduction, and surface roughness in response to variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process based on experimental design. The results showed that RSM can be effectively used to control the forming angle, thickness reduction, and surface roughness.