• Journal of the Korea institute for structural maintenance and inspection
• /
• v.8 no.4
• /
• pp.153-163
• /
• 2004

The main objective of this study is to develop a multi-objective fuzzy optimum design program of steel structures and to verify that the multi-objective fuzzy optimum design is more reasonable than the single objective optimum design in real structural design. In the optimization formulation, the objective functions are both total weight and deflection. The design constraints are derived from the ultimate strength of service ability requirement of AISC-LRFD specification. The structural analysis was performed by the finite element method and also considered geometric non-linearity. The different importance of optimum criteria were reflected with two weighting methods ; membership weighting method and objective weighting method. Thus, designers could choose rational optimum solution of structures with application of two weighting methods.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.22 no.6
• /
• pp.37-44
• /
• 2018

This study proposed the modified weighting values for jointed rock slopes. The studies on deduction of evaluation index and calculation of weighting, development of criteria for evaluation and evaluation models have been conducted through decision making techniques such as the Delphi method and the AHP method by many researchers. Because these decisions making techniques may be less objective, it is necessary to calculate reasonable weighting considering both an objective weighting and a subjective weighting simultaneously. In this study, utilizing the inspection data of jointed rock slopes, an objective weighting that the concept of entropy is applied was calculated. And the subjective weighting values by AHP technique was calculated based on the opinion of experts. And a modified weighting was suggested by combining the two. As a result, it was found that jointed rock slopes have higher weighting in artificial factors and the damage status items. In addition based on the finally suggested weighting (mixed weighting), the revised evaluation criteria could be presented by converting it into the evaluation score (76 points). And it is expected that it could be usefully utilized upon inspections on cutting slopes and safety diagnosis since objective and highly reliable criteria compared to the condition evaluation criteria that are currently used could be presented through the results of the study.

• International Journal of Air-Conditioning and Refrigeration
• /
• v.13 no.2
• /
• pp.71-82
• /
• 2005

The shape of $7\times7$ pin-fins heat sink is optimized numerically to obtain the minimum pressure drop and thermal resistance. In this study, the fin height (h), fin width (w), and fan-to-heat sink distance (c) are chosen as the design variables and the pressure drop $({\Delta}P)$ and thermal resistance $(\theta_j)$ are adopted as the objective functions. To obtain the optimum design values, we used the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem. The results show that the optimum design variables for the weighting coefficient of 0.5 are as follows: W=4.653 mm, h=59.215mm, and c=2.667mm. The objective functions corresponding to the optimal design are calculated as ${\Delta}P=6.82$ Pa and $(\theta_j)=0.56K/W$. The Pareto solutions are also presented for various weighting coefficients and they will offer very useful data to design the pin-fins heat sink.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.701-706
• /
• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Journal of Ship and Ocean Technology
• /
• v.5 no.1
• /
• pp.30-37
• /
• 2001

Ship optimal design is a multi-objective decision-making process and its optimal solution does not exit in general. It is a problem in which the decision-maker is very interested that an effective solution is how to be found which has good characteristic and is substituted for optimal solution in a sense. In the previous methods of multi-objective decision-making, the weighting coefficients are decided from the point of view of individuals which have a bit sub-jective an unilateral behavior. in order to fairly and objectively decide the weighting coeffi-cients, which are considered to be optimal in all system of multi-objective decision-making and satisfactory solution to the decision-maker, the pater presents a method of applying the Technology of the Biggest Entropy. It is proved that the method described in the paper is very feasible and effective be means of a practical example of ship optimal design.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.11a
• /
• pp.334.2-334
• /
• 2002

In conventional model updating using single-objective optimization techniques, imcompatible physical data are compared with each other using weighting factors. There are no general rules fur selecting the weighting factors since they are not directly related with the dynamic behavior of an updated model. So one of the most difficult tasks, in mr)del updating study, is 'balancing among the correlations', i.e. 'trade-off'. (omitted)

• Structural Engineering and Mechanics
• /
• v.65 no.2
• /
• pp.173-181
• /
• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• 한국신재생에너지학회:학술대회논문집
• /
• 2010.11a
• /
• pp.65.1-65.1
• /
• 2010

Thermal performance tests of solar thermal collectors include determination of coefficient parameters in an efficiency equation. The parameters can be estimated using regression method to minimize an objective function as sum of differences between measured efficiency data and regressed efficiency equation. However, this conventional approach doesn't consider measurement uncertainties. In this presentation, a method to determine regression parameters in the efficiency equation and uncertainties of the parameters is described with mainly mathematical expressions based on literature reviews. In the method, parameters in the equation for collector efficiency can be determined using regression analysis with a weighting factor in the objective function. The weighting factor can be uncertainties of the differences between measured and fitted efficiencies. To evaluate the approach, performance estimation of a solar collector using the efficiency equation with uncertainties is compared to the result using the conventional efficiency equation by a simulated way for a case in one of previous studies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.380-383
• /
• 2003

In this paper, we propose a fuzzy group decision making method for multiple decision maker-multiple objective programming problems to obtain the agreeable solution. In the proposed method, considering the vague nature of human subjective judgement it is assumed that each of multiple decision makers has a fuzzy goal for each of his/her own objective functions. After eliciting the membership functions from the decision makers for their fuzzy goals, total M-Pareto optimal solution concept is defined in membership spaces in order to deal with multiple decision maker-multiple objective programming problems. For generating a candidate of the agreeable solution which is total M-Pareto optimal, the extended weighted minimax problem is formulated and solved for some weighting vector which is specified by the decision makers in their subjective manner, Given the total M-Pareto optimal solution, each of the derision makers must either be satisfied with the current values of the membership functions, or update his/her weighting vector, However, in general, it seems to be very difficult to find the agreeable solution with which all of the decision makers are satisfied perfectly because of the conflicts between their membership functions. In the proposed method, each of the decision makers is requested to estimate the degree of satisfaction for the candidate of the agreeable solution. Using the estimated values or satisfaction of each of the decision makers, the core concept is desnfied, which is a set of undominated candidates. The interactive algorithm is developed to obtain the agreeable solution which satisfies core conditions.

• Steel and Composite Structures
• /
• v.25 no.4
• /
• pp.403-413
• /
• 2017

The fabric braided braking hose that delivers the driver's braking force to brake cylinder undergoes the large deformation cyclic motion according to the steering and bump/rebound motions of vehicle. The cyclic large deformation of braking hose may give rise to two critical problems: the interference with other adjacent vehicle parts and the micro cracking stemming from the fatigue damage accumulation. Hence, both the hose deformation and the fatigue damage become the critical issue in the design of braking hose. In this context, this paper introduces a multi-objective optimization method for minimizing the both quantities. The total length of hose and the helix angles of fabric braided composite layers are chosen for the design variables, and the maximum hose deformation and the critical fatigue life cycle are defined by the individual single objective functions. The trade-off between two single objective functions is made by introducing the weighting factors. The proposed optimization method is validated and the improvement of initial hose design is examined through the benchmark simulation. Furthermore, the dependence of optimum solutions on the weighting factors is also investigated.