• Steel and Composite Structures
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• 제47권5호
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Industrial Engineering and Management Systems
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• 제13권1호
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• pp.43-51
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• 2014

This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is $10{\times}10$ JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.487-498
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• 2018

The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권7호
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• pp.327-331
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• 2006

We have proposed an image restoration method for a bi-level waveforms whose number of edges is known to us. Based on the information, we parametrize a bi-level waveform using the locations of edges and restore the waveform by estimating the parameter. We estimated the locations by maximizing the correlation coefficients between the hi-level waveform and the measured waveform. In experiments using two dimensional barcode images of the PDF417 specification, the proposed method showed better performance than conventional methods in the sense that the proposed method was able to decode barcode images that were not decoded by the conventional methods.

• 전기학회논문지
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• 제61권12호
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• pp.1926-1931
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• 2012

We investigated a novel fast non-uniform illumination correction method for bi-level images. The proposed method divides a bi-level image into sub-images and roughly estimates block-wise illumination by low pass filtered maximum values of sub-images. After that, we apply bilinear interpolation using the block-wise illumination to estimate non-uniform illumination, and compensate for the effect of non-uniform illumination using the estimated illumination. Since the proposed method is not based on computation intensive iterative optimization, the proposed method can be used effectively for applications that require fast correction of non-uniform illumination. In simulations, the proposed method showed more than 20 times faster speed than existing entropy minimization method. Moreover, in simulations and experiments, the restored images by the proposed method were more close to true images than images restored by conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1301-1318
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• 2017

In order to utilize the licensed channel of cognitive radio (CR) when the primary user (PU) is detected busy, a benefit-exchange access mode based on cooperative communication is proposed to allow secondary user (SU) to access the busy channel through giving assistance to PU's communication in exchange for some transmission bandwidth. A holistic joint optimization problem is formulated to maximize the total throughput of CR system through jointly optimizing the parameters of cooperative spectrum sensing (CSS), including the local sensing time, the pre-configured sensing decision threshold, the forward power of cooperative communication, and the bandwidth and transmission power allocated to SUs in benefit-exchange access mode and traditional access mode, respectively. To solve this complex problem, a combination of bi-level optimization, interior-point optimization and exhaustive optimization is proposed. Simulation results show that, compared with the tradition throughput maximizing model (TTMM), the proposed holistic joint optimization model (HJOM) can make use of the channel effectively even if PU is busy, and the total throughput of CR obtains a considerable improvement by HJOM.

• 대한교통학회지
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• 제22권7호
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• pp.99-106
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• 2004

본 연구에서는 바이레벨 문제를 풀기 위한 2가지 접근법, 즉 Cournot-Nash 게임과 Stackelbgerg 게임을 서로 비교하기 위한 것으로, 하위문제가 결정적인 통행배정문제(deterministic traffic assignment)인 경우와 확률적 통행배정문제(stochastic traffic assignment)인 경우로 구분하여 분석한다. 바이레벨 프로그램(bi-level program)은 상위문제(upper level program)과 하위 문제(lower level program)로 구성된 수리적인 문제로 상위문제는 목적하는 특정함수를 최적화시키는 형태이며, 하위문제는 통행자의 행태를 반영하는 형태로 구축된다. 기존에 제시된 알고리듬중 바이레벨문제의 대표적인 풀이 알고리듬인 IOA(Iterative Optimization Assignment) 알고리듬과 기종점 통행행렬추정(OD matrix estimation)에 주로 사용되는 IEA(Iterative Estimation Assignment)은 상위문제와 하위문제가 서로 독립적으로 존재하면서 설계변수와 통행량을 서로 주고받는 형태를 갖고 있어 Cournot-Nash 게임형태이다. 이에 반해, 최근에 제시된 민감도분석(Sensitivity analysis)을 기초로 한 알고리듬들은 상위문제에서 결정된 설계변수 변화에 대해 하위문제의 통행량변화를 민감도를 통해 고려하기 때문에 Stackelbeg게임이라고 볼 수 있다. 본 연구에서는 이들 알고리듬들을 비교하는 데 연구의 목적이 있으며, 기존에 제시된 기법과는 다른 좀 더 효율적인 접근법을 제시한다. 예제 교통망을 이용하여 제시된 모형들을 비교해본 결과, 결정적인 통행배정모형을 하위문제로 설정한 경우에는 두가지 접근법 모두 동일한 상위목적함수 값을 보여 우위를 판단할 수 없었지만, 확정적 통행배정모형으로 설정한 경우, Stackelberg게임 접근법이 Cournot-Nash게임 접근법 보다 더 우수함을 확인할 수 있었다.

• 대한교통학회지
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• 제26권2호
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• pp.89-100
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• 2008

교통신호와 개별 통행자의 경로선택은 서로 상호작용하는 관계이다. 통행자의 경로 선택은 교통신호에 따라 결정될 수 있으며 또한 최적의 교통신호 역시 이동류별 교통량에 따라 달라지게된다. 본 연구는 양방향 링크를 포함하는 4현시 교차로로 구성된 네트워크에서 모든 이동류에 대하여 교통신호의 영향을 반영할 수 있는 통행배정 모형을 구축하고 이를 신호최적화 문제와 결합하여 네트워크의 총 지체를 최소화하는 신호제어변수와 통행배정 결과를 산출하는 모형을 bi-level problem으로 구축하였다. 본 연구에서 사용된 경로기반 통행배정 모형은 M.H. Xu 등이 제한한 Column Generation 방법의 일종인 heuristic Equilibrium Assignment 기법을 기반으로 하여 교차로의 이동류별 통행비용을 고려할 수 있도록 수정하여 구성하였으며 지체최소화를 목적함수로하는 신호최적화 방법론으로는 Genetic Algorithm을 사용하였다. 본 모형을 모의네트워크에 적용하여 실험한 결과 네트워크의 통행비용함수를 최소화하는 신호변수와 통행자의 경로선택 결과를 산출하였다.

• Journal of Ship and Ocean Technology
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• 제8권2호
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• pp.41-60
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• 2004

Ship design process requires lots of complicated analyses for determining a large number of design variables. Due to its complexity, the process is divided into several tractable designs or analysis problems. The interdependent relationship requires repetitive works. This paper employs collaborative optimization (CO), one of the multidisciplinary design optimization (MDO) techniques, for treating such complex relationship. CO guarantees disciplinary autonomy while maintaining interdisciplinary compatibility due to its bi-level optimization structure. However, the considerably increased computational time and the slow convergence have been reported as its drawbacks. This paper proposes the use of an approximation model in place of the disciplinary optimization in the system-level optimization. Neural network classification is employed as a classifier to determine whether a design point is feasible or not. Kriging is also combined with the classification to make up for the weakness that the classification cannot estimate the degree of infeasibility. For the purpose of enhancing the accuracy of a predicted optimum and reducing the required number of disciplinary optimizations, an approximation management framework is also employed in the system-level optimization.

• 한국통신학회논문지
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• 제30권4B호
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• pp.178-185
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• 2005

네트워크 단위의 이동성을 지원하는 network mobility (MEMO) 기술에서는 중첩된 네트워크 환경 (nested NEMO)에서 전달 지연 시간을 줄이는 경로를 최적화에 관현 연구가 활발히 이루어지고 있다. 현재 대표적인 경로 최적화 방안으로는 확장 헤드를 이용하여 경로 정보를 모두 기록하는 RRH (Reverse Routing Header)와 최상위 MR에서 하부에 위치한 MR의 상태 정보를 관리하는 BHT (Bi-directional tunnel between Home agent and Top level mobile route)이 제안되어 있다. 하지만 기존의 방안들은 중첩 깊이가 증가할수록 패킷 전달을 위한 오버헤드가 증가하는 문제가 발생한다. 본 논문에서는 중첩된 이동 네트워크 환경에서 지역적 정보를 이용한 경로 최적화 방안 (RIRO; Regional Information-based Route Optimization)을 제안하고자 한다. RIRO 방안에서는 모든 MR들은 자신의 하부에 위치한 MR들의 위치 정보를 관리하고 라우팅 헤더를 이용하여 패킷 전달 경로를 최적화하는 방안으로 중첩된 환경에서도 패킷이 전달을 위한 오버헤더가 증가하지 않는 장점이 있다.