• Title/Summary/Keyword: Self-optimization

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Tree based Route Optimization in Nested NEMO Environment (중첩 NEMO 환경에서 트리 기반 라우트 최적화 기법)

  • Lim, Hyung-Jin;Chung, Tai-Myoung
    • Journal of Internet Computing and Services
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    • v.9 no.1
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    • pp.9-19
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    • 2008
  • This paper propose the issue of connecting nested NEMO (Network Nobility) networks to global IPv6 networks, while supporting IPv6 mobility. Specifically, we consider a self-addressing including topology information IPv6-enabled NEMO infrastructure. The proposed self-organization addressing protocol automatically organized mobile routers into free architecture and configuration their global IPv6 addresses. BU(binding update) to MR own HA and internal rouging, hosed on longest prefix matching and soft state routing cache, are specially designed for IPv6-based NEMO. In conclusion, numeric analysis ore conducted to show more efficiency of the proposed routing protocols than other RO (Route Optimization) approaches.

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Structural Optimization using Improved Higher-order Convex Approximation (개선된 고차 Convex 근사화를 이용한 구조최적설계)

  • 조효남;민대홍;김성헌
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2002.10a
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    • pp.271-278
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    • 2002
  • Structural optimization using improved higer-order convex approximation is proposed in this paper. The proposed method is a generalization of the convex approximation method. The order of the approximation function for each constraint is automatically adjusted in the optimization process. And also the order of each design variable is differently adjusted. This self-adjusted capability makes the approximate constraint values conservative enough to maintain the optimum design point of the approximate problem in feasible region. The efficiency of proposed algorithm, compared with conventional algorithm is successfully demonstrated in the Three-bar Truss example.

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Lightweight Self-consolidating Concrete with Expanded Shale Aggregates: Modelling and Optimization

  • Lotfy, Abdurrahmaan;Hossain, Khandaker M.A.;Lachemi, Mohamed
    • International Journal of Concrete Structures and Materials
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    • v.9 no.2
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    • pp.185-206
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    • 2015
  • This paper presents statistical models developed to study the influence of key mix design parameters on the properties of lightweight self-consolidating concrete (LWSCC) with expanded shale (ESH) aggregates. Twenty LWSCC mixtures are designed and tested, where responses (properties) are evaluated to analyze influence of mix design parameters and develop the models. Such responses included slump flow diameter, V-funnel flow time, J-ring flow diameter, J-ring height difference, L-box ratio, filling capacity, sieve segregation, unit weight and compressive strength. The developed models are valid for mixes with 0.30-0.40 water-to-binder ratio, high range water reducing admixture of 0.3-1.2 % (by total content of binder) and total binder content of $410-550kg/m^3$. The models are able to identify the influential mix design parameters and their interactions which can be useful to reduce the test protocol needed for proportioning of LWSCCs. Three industrial class ESH-LWSCC mixtures are developed using statistical models and their performance is validated through test results with good agreement. The developed ESH-LWSCC mixtures are able to satisfy the European EFNARC criteria for self-consolidating concrete.

Optimal Stiffness Design of Self-Piercing Riveting's C-Frame for Multimaterial Joining (다종소재 접합을 위한 SPR(Self-Piercing Riveting)용 C-프레임 강성 최적설계)

  • Shin, Chang-Yeul;Lee, Jae-Jin;Mun, Ji-Hun;Kwon, Soon-Deok;Yang, Min-Seok;Lee, Jae-Wook
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.5
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    • pp.76-84
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    • 2021
  • In this study, an optimal stiffness model of the C-frame, which was supporting the mold and tool load, was proposed to obtain quality self-piercing riveting (SPR) joining. First, the load path acting on the C-frame structure was identified using topology optimization. Then, a final suggested model was proposed based on the load path results. Stiffness and strength analyses were performed for a rivet pressing force of 7.3 [t] to compare the design performance of the final proposed model with that of the initial model. Moreover, to examine the reliability of continuous and repeated processes, vibration analysis was performed and the dynamic stiffness of the final proposed model was reviewed. Additionally, fatigue analysis was performed to ascertain the fatigue characteristics due to simple repetitive loading. Finally, stiffness test was performed for the final proposed model to verify the analysis results. The obtained results differed from the analysis result by 2.9%. Consequently, the performance of the final proposed model was superior to that of the initial model with respect to not only the SPR fastening quality but also the reliability of continuous and repetitive processes.

Optimum design of multi-span composite box girder bridges using Cuckoo Search algorithm

  • Kaveh, A.;Bakhshpoori, T.;Barkhori, M.
    • Steel and Composite Structures
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    • v.17 no.5
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    • pp.705-719
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    • 2014
  • Composite steel-concrete box girders are frequently used in bridge construction for their economic and structural advantages. An integrated metaheuristic based optimization procedure is proposed for discrete size optimization of straight multi-span steel box girders with the objective of minimizing the self-weight of girder. The metaheuristic algorithm of choice is the Cuckoo Search (CS) algorithm. The optimum design of a box girder is characterized by geometry, serviceability and ultimate limit states specified by the American Association of State Highway and Transportation Officials (AASHTO). Size optimization of a practical design example investigates the efficiency of this optimization approach and leads to around 15% of saving in material.

Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization

  • Tejani, Ghanshyam G.;Savsani, Vimal J.;Patel, Vivek K.;Bureerat, Sujin
    • Advances in Computational Design
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    • v.2 no.4
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    • pp.313-331
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    • 2017
  • In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

Research on the optimization method for PGNAA system design based on Signal-to-Noise Ratio evaluation

  • Li, JiaTong;Jia, WenBao;Hei, DaQian;Yao, Zeen;Cheng, Can
    • Nuclear Engineering and Technology
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    • v.54 no.6
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    • pp.2221-2229
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    • 2022
  • In this research, for improving the measurement performance of Prompt Gamma-ray Neutron Activation Analysis (PGNAA) set-up, a new optimization method for set-up design was proposed and investigated. At first, the calculation method for Signal-to-Noise Ratio (SNR) was proposed. Since the SNR could be calculated and quantified accurately, the SNR was chosen as the evaluation parameter in the new optimization method. For discussing the feasibility of the SNR optimization method, two kinds of PGNAA set-ups were designed in the MCNP code, based on the SNR optimization method and the previous signal optimization method, respectively. Meanwhile, the single element spectra analysis method was proposed, and the analysis effect of single element spectra as well as element sensitivity were used for comparing the measurement performance. Since the simulation results showed the better measurement performance of set-up designed by SNR optimization method, the experimental set-ups were built for the further testing, finally demonstrating the feasibility of the SNR optimization method for PGNAA setup design.

SCALING METHODS FOR QUASI-NEWTON METHODS

  • MOGHRABI, ISSAM A.R.
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.6 no.1
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    • pp.91-107
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    • 2002
  • This paper presents two new self-scaling variable-metric algorithms. The first is based on a known two-parameter family of rank-two updating formulae, the second employs an initial scaling of the estimated inverse Hessian which modifies the first self-scaling algorithm. The algorithms are compared with similar published algorithms, notably those due to Oren, Shanno and Phua, Biggs and with BFGS (the best known quasi-Newton method). The best of these new and published algorithms are also modified to employ inexact line searches with marginal effect. The new algorithms are superior, especially as the problem dimension increases.

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Buckling of cylindrical shells under external pressure proposition of a new shape of self-stiffened shell

  • Araar, M.;Jullien, J.F.
    • Structural Engineering and Mechanics
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    • v.4 no.4
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    • pp.451-460
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    • 1996
  • We propose a new shape of cylindrical shell formed by multiples vaults which gives a self-stiffening against buckling. By an experimental and numerical study of cylindrical shells with a repeated defect, on the circumferential direction made only of outside oriented wave-defects, we show that multiple vault cylindrical shells can have a good behaviour in buckling. An optimal behaviour is obtained by optimization of the vaults number, with conduces to a special multiple vault cylindrical shell named "ASTER shell".

Application of self organizing genetic algorithm

  • Jeong, Il-Kwon;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.18-21
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    • 1995
  • In this paper we describe a new method for multimodal function optimization using genetic algorithms(GAs). We propose adaptation rules for GA parameters such as population size, crossover probability and mutation probability. In the self organizing genetic algorithm(SOGA), SOGA parameters change according to the adaptation rules. Thus, we do not have to set the parameters manually. We discuss about SOGA and those of other approaches for adapting operator probabilities in GAs. The validity of the proposed algorithm will be verified in a simulation example of system identification.

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