• Title/Summary/Keyword: Optimization theory

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Topology optimization of multiphase elastic plates with Reissner-Mindlin plate theory

  • Banh, Thanh T.;Lee, Dongkyu;Lee, Jaehong;Kang, Joowon;Shin, Soomi
    • Smart Structures and Systems
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    • v.22 no.3
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    • pp.249-257
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    • 2018
  • This study contributes to evaluate multiphase topology optimization design of plate-like elastic structures with constant thickness and Reissner-Mindlin plate theory. Stiffness and adjoint sensitivity formulations linked to Reissner-Mindlin plate potential energy of bending and shear are derived in terms of multiphase design variables. Multiphase optimization problem is solved through alternative active-phase algorithm with Gauss-Seidel version as an optimization model of optimality criteria. Numerical examples verify efficiency and diversity of the present topology optimization method of Reissner-Mindlin elastic plates depending on multiphase and Poisson's ratio.

Game Theory Based Coevolutionary Algorithm: A New Computational Coevolutionary Approach

  • Sim, Kwee-Bo;Lee, Dong-Wook;Kim, Ji-Yoon
    • International Journal of Control, Automation, and Systems
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    • v.2 no.4
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    • pp.463-474
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    • 2004
  • Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

Case Studies of Nonlinear Response Structural Optimization Using Equivalent Loads (등가하중법을 이용한 비선형 반응 구조최적설계 사례연구)

  • Kim, Yong-Il;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.11
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    • pp.1059-1068
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    • 2007
  • Nonlinear response structural optimization is performed using equivalent loads (NROEL). Nonlinear response optimization is extremely cost because many nonlinear analyses are required. In NROEL, the external loads are transformed to the equivalent loads (EL) for linear static analysis and linear response optimization is carried out based on the EL in a cyclic manner until the convergence criteria are satisfied. EL is the load set which generates the same response field of linear analysis as that of nonlinear analysis. The primitive from of theory has been published. In this research, the theory is investigated with large scale example problems. Four examples are solved by using NROEL. Conventional optimization with sensitivity analysis using the finite difference method (FDM) is also applied to the same examples. Moreover, response surface optimization method is applied to the last two examples. The results of the optimizations are compared. In nonlinear response optimization of large scale problems, hundreds (or even thousands) of nonlinear analyses are expected to satisfy the convergence criteria. However, in nonlinear response optimization using equivalent loads, only tens of nonlinear analyses are required. The results are discussed and the usefulness of NROEL is presented.

Propeller Skew Optimization Considering Varying Wake Field (선체반류를 고려한 프로펠러 최적 스큐화)

  • 문일성;김건도;유용완;류민철;이창섭
    • Journal of the Society of Naval Architects of Korea
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    • v.40 no.5
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    • pp.26-35
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    • 2003
  • Propellers operating in a given nonuniform ship wake generate unsteady loads leading to undesirable stern vibration problems. The skew is known to be the most proper and effective geometric parameter to control or reduce the fluctuating forces on the shaft. This paper assumes the skew profile as either a quadratic or a cubic function of the radius and determines the coefficients of the polynomial function by applying the simplex method. The method uses the converted unconstrained algorithm to solve the constrained minimization problem of 6-component shaft excitation forces. The propeller excitation was computed either by applying the two-dimensional gust theory for quick estimation or by the fully three-dimensional unsteady lifting surface theory in time domain for an accurate solution. A sample result demonstrates that the shaft forces can be further reduced through optimization from the original design.

Fuzzy Modeling by Genetic Algorithm and Rough Set Theory (GA와 러프집합을 이용한 퍼지 모델링)

  • Joo, Yong-Suk;Lee, Chul-Heui
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.333-336
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    • 2002
  • In many cases, fuzzy modeling has a defect that the design procedure cannot be theoretically justified. To overcome this difficulty, we suggest a new design method for fuzzy model by combining genetic algorithm(GA) and mush set theory. GA, which has the advantages is optimization, and rule base. However, it is some what time consuming, so are introduce rough set theory to the rule reduction procedure. As a result, the decrease of learning time and the considerable rate of rule reduction is achieved without loss of useful information. The preposed algorithm is composed of three stages; First stage is quasi-optimization of fuzzy model using GA(coarse tuning). Next the obtained rule base is reduced by rough set concept(rule reduction). Finally we perform re-optimization of the membership functions by GA(fine tuning). To check the effectiveness of the suggested algorithm, examples for time series prediction are examined.

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Frequency optimization for laminated composite plates using extended layerwise approach

  • Topal, Umut
    • Steel and Composite Structures
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    • v.12 no.6
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    • pp.541-548
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    • 2012
  • This paper deals with the applicability of extended layerwise optimization method (ELOM) for frequency optimization of laminated composite plates. The design objective is the maximization of the fundamental frequency of the laminated plates. The fibre orientations in the layers are considered as design variables. The first order shear deformation theory (FSDT) is used for the finite element solution of the laminates. Finally, the numerical analysis is carried out to show the applicability of extended layerwise optimization algorithm of laminated plates for different parameters such as plate aspect ratios and boundary conditions.

GAME MODEL AND ITS SOLVING METHOD FOR OPTIMAL SCALE OF POWER PLANTS ENTERING GENERATION POWER MARKET

  • Tan, Zhongfu;Chen, Guangjuan;Li, Xiaojun
    • Journal of applied mathematics & informatics
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    • v.26 no.1_2
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    • pp.337-347
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    • 2008
  • Based on social welfare maximum theory, the optimal scale of power plants entering generation power market being is researched. A static non-cooperative game model for short-term optimization of power plants with different cost is presented. And the equilibrium solutions and the total social welfare are obtained. According to principle of maximum social welfare selection, the optimization model is solved, optimal number of power plants entering the market is determined. The optimization results can not only increase the customer surplus and improve power production efficiency, but also sustain normal profits of power plants and scale economy of power production, and the waste of resource can also be avoided. At last, case results show that the proposed model is efficient.

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Application of the Infinite Dimensional Optimization to Marine Propellers and Its Mathematical Uniqueness (무한차원최적화의 추진기에의 응용과 그의 수학적 유일성 고찰)

  • Jang, Taek-S.;Hong, Sa-Y.
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2002.05a
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    • pp.231-236
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    • 2002
  • By using the infinite dimensional optimization[Jang and Kinoshita(2000)]. which is based on the Hilbert space theory, optimal marine propellers are studied. The mathematical uniqueness for the optimized propeller is shown in this study. As a numerical example, the MAU type propeller is considered and used as the initial guess for the optimization method. The numerical results for an optimal marine propeller is illustrated for the pitch distribution.

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Optimization of Composite Laminated Plate Using Fuzzy Set Theory (퍼지 이론을 이용한 복합재 적층판의 최적설계)

  • 홍영기;이종호;구만회;우호길
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 1999.11a
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    • pp.63-67
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    • 1999
  • This paper presents the optimization of CFRP laminated rectangular plates using fuzzy theory. In optimization, thickness of CFRP lamina and fiber angle are taken as design variables, and total thickness of the plates is minimized under Tsai-Hill failure criterion. The uncertainties are entered by introducing fuzzy material strengths and then the objective and constraints are represented by a membership function of their own according to the intersection method. Various design results are presented for the CFRP laminated composites plates.

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AN LMI APPROACH TO AUTOMATIC LOOP-SHAPING OF QFT CONTROLLERS

  • Bokharaie, Vaheed S.;Khaki-Sedigh, Ali
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.433-437
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    • 2003
  • Quantitative Feedback Theory (QFT) is one of effective methods of robust controller design. In QFT design we can considers the phase information of the perturbed plant so it is less conservative than $H_{\infty}$ and ${\mu}$-synthesis methods and as be shown, it is more transparent than the sensitivity reduction methods mentioned . In this paper we want to overcome the major drawback of QFT method which is lack of an automatic method for loop-shaping step of the method so we focus on the following problem: Given a nominal plant and QFT bounds, synthesize a controller that achieves closed-loop stability and satisfies the QFT boundaries. The usual approach to this problem involves loop-shaping in the frequency domain by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. Clearly such an automatic process must involve some sort of optimization, and while recent results on convex optimization have found fruitful applications in other areas of control theory we have tried to use LMI theory for automating the loop-shaping step of QFT design.

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