• Proceedings of the KSME Conference
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• 2007.05a
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• pp.349-353
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• 2007

The main functions of excavator are mainly carried out by excavator attachments such as arm and boom. These components should be designed to be light as well as durable enough because their effects on the whole structure are significant. In this paper, an optimization procedure for lightweight design considering fatigue strength for excavator attachments is presented. The weight of attachments and allowable fatigue stresses at critical areas are used as objective function and constraints, respectively, in which design variables are the thickness of the plates of attachments. The simulated annealing search method is adopted for a global optimization solution. Besides, the response surface method using the artificial neural network is used to simulate constraint function for the sake of practical fast calculation. Some example case of optimization is presented here for a sample excavator. This weight optimization is expected to contribute to a considerable improvement of fuel efficiency of excavator.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• Korean System Dynamics Review
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• v.13 no.2
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• pp.47-71
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• 2012

The purpose of this research is the examination of validity of data as well as simulation model, i.e. to simulate the real data in the SD model with the least error using the adjustments for the faithful reflection of real data to the simulation. In general, SD programs (e.g. VENSIM) utilize the Euler or Runge-Kutta method as an algorithm. It is possible to reflect the trend of real data via these two estimation methods however can cause the validity problem in case of the simulation requiring the accuracy as they have endogenous errors. In this article, the future population estimated by the Korea National Statistical Office (KNSO) to 2050 is simulated by the aging chain model, dividing the population into three cohorts, 0-14, 15-64, 65 and over cohorts by age and offering the adjustments to them. Adjustments are calculated by optimization with three different methods, optimization in EXCEL, manual optimization with iterative calculation, and optimization in VENSIM DSS, the results are compared, and at last the optimal adjustment set with the least error are found among them. The simulation results with the pre-determined optimal adjustment set are validated by methods proposed by Barlas (1996) and other alternative methods. It is concluded that the result of simulation model in this research has no significant difference from the real data and reflects the real trend faithfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5972-5989
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• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.734-745
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• 2021

In order to achieve a good and competitive FPSO design, the building cost and the motion performances are the two most critical and conflicting KPIs to be considered. In this study, the author's previous work (Lee, et al., 2021) on the optimization of an FPSO's hull dimensions with 1800 MBBLs storage capacity at Brazil field was extended using a multi-objective parametric optimization with the hull steel weight and the operability which are closely related to the building cost and the operational cost during the lifetime, respectively. For the purpose of more realistic and practical FPSO design, the constraints related to crew comfort and the safe helicopter take-off and landing operation were newly added. Also, the green water on deck was calculated accurately to check the suitability of the designed freeboard height using a newly developed real-time calculation module for the relative wave elevations. With aids of this updated optimization formulation, we presented multiple optimal FPSO dimensions expressed as a Pareto set which aids FPSO designers to conveniently select the practical and competitive dimensions. The excellence of the developed approach was verified by comparing the optimization results with those of FPSOs dimensioned for operation at West Africa and Brazil field.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.7
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• pp.785-794
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• 2005

Modern ship hulls of large oil carriers and container carrers have become more flexible with scantling optimization and increase in ship length. On the other hand. as the demand for power has increased with the ship size. shaft diameters have become larger and stiffer. Consequently. the alignment of the propulsion system has become more sensitive to hull girder deflections. resulting in difficulties in analyzing the alignment and conducting the alignment procedure. Accordingly. the frequency of shaft alignment related bearing damages has increased significantly in recent years. The alignment related damages are mostly attributed to inadequate analyses. changes in the design of the vessel. shipyards' practices in conducting the alignment. and a lack of well defined analytical criteria. The hull deflections should be considered at the design stage to minimize the bearing damage caused by hull deflection. Hull deflections can be estimated by analytical approach and reverse calculation using the measured data. The hull girder deflection analysis using the reverse calculation will be introduced in this paper.

• Bulletin of the Korean Chemical Society
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• v.2 no.2
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• pp.46-48
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• 1981

CNDO/2 calculation was carried out on hexafluorocyclopropane, tetrafluorocyclopropene, 1,2-dichlorodifluorocyclopropene and 1-lithio-2-chlorodifluorocyclopropene. A partial geometry optimization was carried out on 1-lithio-2-chlorodifluorocyclopropene.

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

• Earthquakes and Structures
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• v.4 no.4
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• pp.341-363
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• 2013

Earthquake response calculation, parametric analysis and seismic parameter optimization of base-isolated structures are some critical issues for seismic design of base-isolated structures. To calculate the earthquake responses for such non-symmetric and non-classical damping linear systems and to implement the earthquake resistant design codes, a modified complex mode superposition design response spectrum method is put forward. Furthermore, to do parameter optimization for base-isolation structures, a graphical approach is proposed by analyzing the relationship between the base shear ratio of a seismic base-isolation floor to non-seismic base-isolation one and frequency ratio-damping ratio, as well as the relationship between the seismic base-isolation floor displacement and frequency ratio-damping ratio. In addition, the influences of mode number and site classification on the seismic base-isolation structure and corresponding optimum parameters are investigated. It is demonstrated that the modified complex mode superposition design response spectrum method is more precise and more convenient to engineering applications for utilizing the damping reduction factors and the design response spectrum, and the proposed graphical approach for parameter optimization of seismic base-isolation structures is compendious and feasible.

• Computers and Concrete
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• v.9 no.2
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• pp.119-131
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• 2012

Optimum packing of aggregate is an important aspect of mixture design, since porosity may be reduced and strength improved. It may also cause a reduction in paste content and is thus of economic relevance too. Several mathematic packing models have been developed in the literature for optimization of mixture design. However in this study, numerical simulation will be used as the main tool for this purpose. A basic, simple theoretical model is used for approximate assessment of mixture optimization. Calculation and simulation will start from a bimodal mixture that is based on the mono-sized packing experiences. Tri-modal and multi-sized particle packing will then be discussed to find the optimum mixture. This study will demonstrate that computer simulation is a good alternative for mixture design and optimization when appropriate particle shapes are selected. Although primarily focusing on aggregate, optimization of blends of Portland cement and mineral admixtures could basically be approached in a similar way.