• 호남수학학술지
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• 제35권2호
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• pp.235-249
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• 2013

It is well known that each kernel function defines primal-dual interior-point method (IPM). Most of polynomial-time interior-point algorithms for linear optimization (LO) are based on the logarithmic kernel function ([9]). In this paper we define new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has $\mathcal{O}(({\log}\;p)^{\frac{5}{2}}\sqrt{n}{\log}\;n\;{\log}\frac{n}{\epsilon})$ and $\mathcal{O}(q^{\frac{3}{2}}({\log}\;p)^3\sqrt{n}{\log}\;\frac{n}{\epsilon})$ iteration complexity for large- and small-update methods, respectively. These are currently the best known complexity results for such methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• 대한수학회지
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• 제47권1호
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• pp.17-28
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• 2010

In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.

• 한국강구조학회 논문집
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• 제10권4호통권37호
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• pp.657-666
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• 1998

본 연구는 변위제약조건을 고려한 강구조물의 최적화를 위하여 효율적인 쌍대알고리즘을 제시한다. 쌍대법은 최적화 문제를 하나의 간단한 대수학적인 형태를 가지는 근사화된 양함수형태의 부문제로 대치할 수 있고, 이때 각 부문제는 볼록면을 가지며 분리 가능한 형태이기 때문에 쌍대알고리즘을 적용함으로써 효과적으로 풀려질 수 있다는 개념에 근거한다. 특히, 본 연구는 양함수형태의 변위제약조건식을 설정하기 위해 가상일의 원리를 적용하고자하며 아울러 쌍대알고리즘내에 단면특성관계를 나타내는 선형회귀식을 추가하여 설계변수의 수를 감소시켜 주고자 한다. 또한 부재선정을 위해 상용화된 표준 철골 단면을 검토함으로써 이산형 최적화문제도 고려한다. 이러한 연구 결과는 기존의 해석기법인 최적정기준법과 비교검토된다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.141-146
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• 1999

A new method, so called MMA(Method of Moving Asymptotes) was applied to the optimization problems of non-linear functions and non-linear structures. In each step of the iterative process, tile MMA generates a strictly convex approximation subproblems and solves them by using the dual problems. The generation of these subproblems is controlled by so called 'moving asymptotes', which may both make no oscillation and speed up tile convergence rate of optimization process. By contrast in generalized dual function, the generated function by MMA is always explicit type. Both the objective and behaviour constraints which were approximated are optimized by dual function. As the results of some examples, it was found that this method is very effective to obtain the global solution for problems with many local solutions. Also it was found that MMA is a very effective approximate method using the original function and its 1st derivatives.

• East Asian mathematical journal
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• 제31권5호
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• pp.737-742
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• 2015

In this paper, we consider a generalized fractional robust optimization problem (FP). Establishing a nonfractional optimization problem (NFP) equivalent to (FP), we establish necessary optimality conditions and duality results.

• 전기학회논문지
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• 제57권6호
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• pp.915-923
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• 2008

This paper focuses on optimal tuning of nonlinear parameters of a dual-input power system stabilizer(dual-input PSS), which can improve the system damping performance immediately following a large disturbance. Until recently, various PSS models have developed to bring stability and reliability to power systems, and some of these models are used in industry applications. However, due to non-smooth nonlinearities from the interaction between linear parameters(gains and time constants of linear controllers) and nonlinear parameters(saturation output limits), the output limit parameters cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures('trial and error' approach) have been used. Therefore, the steepest descent method is applied to implement the optimal tuning of the nonlinear parameters of the dual-input PSS. The gradient required in this optimization technique can be computed from trajectory sensitivities in hybrid system modeling with the differential-algebraic-impulsive-switched(DAIS) structure. The optimal output limits of the dual-input PSS are evaluated by time-domain simulation in both a single machine infinite bus(SMIB) system and a multi-machine power system in comparison with those of a single-input PSS.

• 한국자동차공학회논문집
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• 제18권5호
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• pp.136-144
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• 2010

Exhaust gas recirculation (EGR) is an emission control technology allowing significant NOx emission reduction from light-and heavy duty diesel engines. The future EGR type, dual loop EGR, combining features of high pressure loop EGR and low pressure loop EGR, was developed and optimized by using a commercial engine simulation program, GT-POWER. Some variables were selected to control dual loop EGR system such as VGT (Variable Geometry Turbocharger)performance, especially turbo speed, flap valve opening diameter at the exhaust tail pipe, and EGR valve opening diameter. Applying the dual loop EGR system in the light-duty diesel engine might cause some problems, such as decrease of engine performance and increase of brake specific fuel consumption (BSFC). So proper EGR rate (or mass flow) control would be needed because there are trade-offs of two types of the EGR (HPL and LPL) features. In this study, a diesel engine under dual loop EGR system was optimized by using design of experiment (DoE). Some dominant variables were determined which had effects on torque, BSFC, NOx, and EGR rate. As a result, optimization was performed to compensate the torque and BSFC by controlling start of injection (SOI), injection mass and EGR valves, etc.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2014년도 제49회 KOSCO SYMPOSIUM 초록집
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• pp.141-142
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• 2014

This numerical study was carried out to optimize dual fuel combustion on natural gas-diesel in static chamber. Spray experiments conducted under conditions of premixed methan 0%, 5% and 10%. In the results, penetration decreases when premixed methane is increasing. Constants of numerical models were acquired from results of spray experiments to enhance accuracy of numerical study. And dual fuel engine simulation was implemented by using AVL-FIRE with acquired constants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4595-4610
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• 2020

In the practical communication environment, the accurate channel state information (CSI) is difficult to obtain, which will cause the mismatch of resource and degrade the system performance. In this paper, to account for the channel uncertainties, a robust power allocation scheme for a downlink Non-orthogonal multiple access (NOMA) heterogeneous network (HetNet) is designed to maximize energy efficiency (EE), which can ensure the quality of service (QoS) of users. We conduct the robust optimization model based on worse-case method, in which the channel gains belong to certain ellipsoid sets. To solve the non-convex non-liner optimization, we transform the optimization problem via Dinkelbach method and sequential convex programming, and the power allocation of small cell users (SCUs) is achieved by Lagrange dual approach. Finally, we analysis the convergence performance of proposed scheme. The simulation results demonstrate that the proposed algorithm can improve total EE of SCUs, and has a fast convergence performance.