• Title/Summary/Keyword: Class Optimization

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Optimal Intelligent Digital Redesign for a Class of Fuzzy-Model-Based Controllers

  • Chang-wook;Joo, Young-hoon;Park, Jin-bae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.1 no.1
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    • pp.113-118
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    • 2001
  • In this paper, we develop an optimal intelligent digital redesign method for a class of fuzzy-model-based controllers, effective for stabilization of continuous-time complex nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to extend the results of the classical digital redesign technique to complex nonlinear systems. Unlike the conventional intelligent digital redesign technique reported in the literature, the proposed method utilized the recently developed LMI optimization technique to obtain a digitally redesigned fuzzy-model-based controller. Precisely speaking, the intelligent digital redesign problem is converted to an equivalent optimization problem, and the LMI optimization method is used to find the digitally redesigned fuzzy-model-based controller. A numerical example is provided to evaluate the feasibility of the proposed approach.

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ON OPTIMALITY OF GENERALIZED OPTIMIZATION PROBLEMS ASSOCIATED WITH OPERATOR AND EXISTENCE OF (Tη; ξθ)-INVEX FUNCTIONS

  • Das, Prasanta Kumar
    • East Asian mathematical journal
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    • v.33 no.1
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    • pp.83-102
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    • 2017
  • The main purpose of this paper is to introduce a pair new class of primal and dual problem associated with an operator. We prove the sufficient optimality theorem, weak duality theorem and strong duality theorem for these problems. The equivalence between the generalized optimization problems and the generalized variational inequality problems is studied in ordered topological vector space modeled in Hilbert spaces. We introduce the concept of partial differential associated (PDA)-operator, PDA-vector function and PDA-antisymmetric function to show the existence of a new class of function called, ($T_{\eta};{\xi}_{\theta}$)-invex functions. We discuss first and second kind of ($T_{\eta};{\xi}_{\theta}$)-invex functions and establish their existence theorems in ordered topological vector spaces.

A Study on the Design and Structure Optimization of an Automatic Mooring System for a 6000 ton Class Autonomous Ship (6000톤급 자율운항선박을 위한 자동계류장치 설계 및 구조 최적화에 대한 연구)

  • Kim, Namgeon;Shin, Haneul;Kim, Teagyun;Park, Jihyuk
    • The Journal of Korea Robotics Society
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    • v.17 no.4
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    • pp.493-499
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    • 2022
  • This paper presents the design for the kinematic structure of a system for an automatically moored 6000 ton autonomous ship in a port, and the process and results of optimal design for the link cross-sectional shape. We propose an automatic mooring system with a PPP type serial manipulator structure capable of linear motion in the XYZ axis. The mooring force applied by the mooring system was derived with dynamics simulation tool "ADAMS". The design goal is the minimization of the cross-sectional area of the link. Constrains include compressive stress and shear stress. The optimization problems were solved by using the sequential quadratic programing method implemented in the fmincon package. The shape of the cross section was assumed to be rectangle. Through future research, we plan to manufacture automatic mooring system for 6000ton class autonomous ship.

OPTIMALITY AND DUALITY FOR NONDIFFERENTIABLE FRACTIONAL PROGRAMMING WITH GENERALIZED INVEXITY

  • Kim, Gwi Soo;Kim, Moon Hee
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.3
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    • pp.465-475
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    • 2016
  • We establish necessary and sufficient optimality conditions for a class of generalized nondifferentiable fractional optimization programming problems. Moreover, we prove the weak and strong duality theorems under (V, ${\rho}$)-invexity assumption.

A Heuristic Algorithm for the Reliability Optimization of a Distributed Communication Network

  • Hung, Chih-Young;Yang, Jia-Ren;Park, Dong-Ho;Liu, Yi-Hsin
    • International Journal of Reliability and Applications
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    • v.9 no.1
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    • pp.1-5
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    • 2008
  • A heuristic algorithm for reliability optimization of a distributed network system is developed so that the reliability of a large system can be determined efficiently. This heuristic bases on the determination of maximal reliability set of maximum node capacity, maximal link reliability and maximal node degree.

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A Study on Informediated code for Analyzing Bytecodes (바이트코드 분석을 위한 중간코드에 관한 연구)

  • Kim, Kyung-Soo;Yoo, Weon-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.1 s.39
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    • pp.107-117
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    • 2006
  • Java language creates class files through Java compiler. Class files include informations involved with achievement of program. We can do analysis and optimization for efficient codes by analyzing class files. This paper analyzes bytecodes using informations of Java class files. We translate stack-based Java bytecodes into 3-address codes. Then we translate into static single assignment form using the 3-address codes. Static single assignment form provides a compact representation of a variable's definition-use information. Static single assignment form is often used as an intermediate representation during code optimization. Static sing1e assignment form renames each occurrence of a variable such that each variable is defined only once.

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Portfolio Optimization with Groupwise Selection

  • Kim, Namhyoung;Sra, Suvrit
    • Industrial Engineering and Management Systems
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    • v.13 no.4
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    • pp.442-448
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    • 2014
  • Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.

Computational Methods for On-Node Performance Optimization and Inter-Node Scalability of HPC Applications

  • Kim, Byoung-Do;Rosales-Fernandez, Carlos;Kim, Sungho
    • Journal of Computing Science and Engineering
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    • v.6 no.4
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    • pp.294-309
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    • 2012
  • In the age of multi-core and specialized accelerators in high performance computing (HPC) systems, it is critical to understand application characteristics and apply suitable optimizations in order to fully utilize advanced computing system. Often time, the process involves multiple stages of application performance diagnosis and a trial-and-error type of approach for optimization. In this study, a general guideline of performance optimization has been demonstrated with two class-representing applications. The main focuses are on node-level optimization and inter-node scalability improvement. While the number of optimization case studies is somewhat limited in this paper, the result provides insights into the systematic approach in HPC applications performance engineering.

Structural Dynamic Optimization Using a Genetic Algorithm(GA) (유전자 알고리즘(GA)을 이용한 구조물의 동적해석 및 최적화)

  • 이영우;성활경
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.5
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    • pp.93-99
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    • 2000
  • In many dynamic structural optimization problems, the goal is to reduce the total weight of the structure without causing the resonance. Up to now, gradient informations(i.e., design sensitivity) have been used to achieve the goal. For some class of dynamic problems, especially coalescent eigenvalue Problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique fur structural dynamic modification using a mode modification method with Genetic Algorithm(GA). In GA formulation, fitness is defined based on penalty function approach. Design variables are iteratively improved by using genetic algorithm. Two numerical examples are shown, (ⅰ) a cantilevered plate, and (ⅱ) H-shaped structure. The results demonstrate that the proposed method is highly efficient.

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