• Title, Summary, Keyword: Global optimization

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Design of Two-group Zoom Lens System with Wide Angle of View Using Global Structure Function (전역구조함수를 사용한 광각 2군 줌 렌즈의 설계)

  • Kwon, Hyuk-Joon;Rim, Cheon-Seog
    • Korean Journal of Optics and Photonics
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    • v.20 no.6
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    • pp.319-327
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    • 2009
  • We introduce a new design technique by treating a two-group zoom lens system with a wide angle of view. First, the concept of the global optimization is introduced in the initial design stage, and from this, the global design technique is completed by analyzing and summarizing large quantities of modern design data. That is, we define the global structure function to achieve a new conceptual design technique for global optimization. And the function is put in a simple form by referring lots of patent data, manipulated with other algebraic equations, and solved finally such that we obtain the global solution region. The global solution region corresponds to the global optimization and suggests insightful systematized directions for the design of two-group zoom lens systems. These directions are attractive compared to global optimization.

A B-spline based Branch & Bound Algorithm for Global Optimization (전역 최적화를 위한 B-스플라인 기반의 Branch & Bound알고리즘)

  • Park, Sang-Kun
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.1
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    • pp.24-32
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    • 2010
  • This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

Hull Form Optimization using Parametric Modification Functions and Global Optimization (전역 최적화기법과 파라메트릭 변환함수를 이용한 선형 최적화)

  • Kim, Hee-Jung;Chun, Ho-Hwan;An, Nam-Hyun
    • Journal of the Society of Naval Architects of Korea
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    • v.45 no.6
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    • pp.590-600
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    • 2008
  • This paper concerns the development of a designer friendly hull form parameterization and its coupling with advanced global optimization algorithms. As optimization algorithms, we choose the Partial Swarm Optimization(PSO) recently introduced to solve global optimization problems. Most general-purpose optimization softwares used in industrial applications use gradient-based algorithms, mainly due to their convergence properties and computational efficiency when a relatively few number of variables are considered. However, local optimizers have difficulties with local minima and non-connected feasible regions. Because of the increase of computer power and of the development of efficient Global Optimization (GO) methods, in recent years nongradient-based algorithms have attracted much attention. Furthermore, GO methods provide several advantages over local approaches. In the paper, the derivative-based SQP and the GO approach PSO are compared with their relative performances in solving some typical ship design optimization problem focusing on their effectiveness and efficiency.

A Global Robust Optimization Using the Kriging Based Approximation Model (크리깅 근사모델을 이용한 전역적 강건최적설계)

  • Park Gyung-Jin;Lee Kwon-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9
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    • pp.1243-1252
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    • 2005
  • A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

Individual and Global Optimization of Switched Flux Permanent Magnet Motors

  • Zhu, Z.Q.;Liu, X.
    • Journal of international Conference on Electrical Machines and Systems
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    • v.1 no.1
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    • pp.32-39
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    • 2012
  • With the aid of genetic algorithm (GA), global optimization with multiple geometry parameters is feasible in the design of switched flux permanent magnet (SFPM) machines. To investigate the advantages of global optimization over individual optimization, which has been used extensively for the design of SFPM machines, a comparison between the two approaches is carried out for the case of fixed copper loss and volume. In the case of individual parameter optimization, the sequence in which the individual parameters are optimized is very important. In the global optimization a better design can always be achieved although the corresponding torque density is found to be only slightly better than that of individually optimized with correct design sequence. By using the obtained global optimization results, the performance in machines having two types of stator and rotor pole combinations, i.e. 12/10 and 12/14, are compared, and it is shown that higher torque is exhibited in the 12/14 SFPM machine. Finally, this paper also demonstrates that global optimization, with the restriction of equal pole width, magnet thickness and slot opening, can maximize the torque density without significantly sacrificing other performance, such as cogging torque and overload capability.

On the Global Convergence of Univariate Dynamic Encoding Algorithm for Searches (uDEAS)

  • Kim, Jong-Wook;Kim, Tae-Gyu;Choi, Joon-Young;Kim, Sang-Woo
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.571-582
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    • 2008
  • This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

Optimization Analysis of Trajectory for Re-Entry Vehicle Using Global Orthogonal Polynomial

  • Lee Dae-Woo
    • Journal of Mechanical Science and Technology
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    • v.20 no.10
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    • pp.1557-1566
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    • 2006
  • We present a procedure for the application of global orthogonal polynomial into an atmospheric re-entry maneuvering problem. This trajectory optimization is imbedded in a family of canonically parameterized optimal control problem. The optimal control problem is transcribed to nonlinear programming via global orthogonal polynomial and is solved a sparse nonlinear optimization algorithm. We analyze the optimal trajectories with respect to the performance of re-entry maneuver.

A Global Optimization Technique for the Capacitor Placement in Distribution Systems (배전계통 커패시터 설치를 위한 전역적 최적화 기법)

  • Rhee, Sang-Bong;Kim, Kyu-Ho;Lee, Sang-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.5
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    • pp.748-754
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    • 2008
  • The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, a global optimization technique, which employing the chaos search algorithm, is applied to solve optimal capacitor placement problem with reducing computational effort and enhancing global optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

Global Optimization of Composite Structures Using Triangular Patch Algorithm (삼각 패치 알고리듬을 이용한 복합 재료 구조물의 전체 최적화)

  • O, Seung-Hwan;Lee, Byeong-Chae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.4
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    • pp.671-684
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    • 2001
  • Several design problems of composite structures are studied via a global optimizer based on attraction regions. MSC/NASTRAN is adopted for static and eigenvalue analysis. The method of modified feasible direction in DOT is used for local optimization. Through the review of global optimization algorithms, the triangular patch algorithm is selected because the algorithm is known to be efficient, robust and powerful for general nonlinear optimization problems. For general applicability, various mechanical properties are considered as design objectives; strain energy, eigenvalue, weight, displacement, and buckling load. In all cases considered, the triangular patch algorithm results in a lot of optimum points and useful design patterns, that are not easy by local algorithms or conventional global algorithms can be determined.

Utilizing Soft Computing Techniques in Global Approximate Optimization (전역근사최적화를 위한 소프트컴퓨팅기술의 활용)

  • 이종수;장민성;김승진;김도영
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • pp.449-457
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    • 2000
  • The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

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