• Title/Summary/Keyword: Linear Optimization

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Economic Dispatch Using Hybrid Particle Swarm Optimization with Prohibited Operating Zones and Ramp Rate Limit Constraints

  • Prabakaran, S.;Senthilkuma, V.;Baskar, G.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.4
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    • pp.1441-1452
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    • 2015
  • This paper proposes a new Hybrid Particle Swarm Optimization (HPSO) method that integrates the Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) techniques. The proposed method is applied to solve Economic Dispatch(ED) problems considering prohibited operating zones, ramp rate limits, capacity limits and power balance constraints. In the proposed HPSO method, the best features of both EP and PSO are exploited, and it is capable of finding the most optimal solution for the non-linear optimization problems. For validating the proposed method, it has been tested on the standard three, six, fifteen and twenty unit test systems. The numerical results show that the proposed HPSO method is well suitable for solving non-linear economic dispatch problems, and it outperforms the EP, PSO and other modern metaheuristic optimization methods reported in the recent literatures.

Optimal Cooling Operation of a Single Family House Model Equipped with Renewable Energy Facility by Linear Programming (신재생에너지 단독주택 모델 냉방운전의 선형계획법 기반 운전 최적화 연구)

  • Shin, Younggy;Kim, Eui-Jong;Lee, Kyoung-ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.29 no.12
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    • pp.638-644
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    • 2017
  • Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

Optimization of inlet velocity profile for uniform epitaxial growth (균일한 에피층 성장을 위한 입구 유속분포 최적화)

  • Cho W. K.;Choi D. H.;Kim M.-U.
    • 한국전산유체공학회:학술대회논문집
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    • 1998.11a
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    • pp.121-126
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    • 1998
  • A numerical optimization procedure is developed to find the inlet velocity profile that yields the most uniform epitaxial layer in a vertical MOCVD reactor. It involves the solution of fully elliptic equations of motion, temperature, and concentration; the finite volume method based on SIMPLE algorithm has been adopted to solve the Navier-Stokes equations. The overall optimization process is highly nonlinear and has been efficiently treated by the sequential linear programming technique that breaks the non-linear problem into a series of linear ones. The optimal profile approximated by a 6th-degree Chebyshev polynomial is very successful in reducing the spatial non-uniformity of the growth rate. The optimization is particularly effective to the high Reynolds number flow. It is also found that a properly constructed inlet velocity profile can suppress the buoyancy driven secondary flow and improve the growth-rate uniformity.

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Neural Networks for Optimization Problem with Nonlinear Constraints (비선형제한조건을 갖는 최적화문제 신경회로망)

  • Kang, Min-Je
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.1
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    • pp.1-6
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    • 2002
  • Hopfield introduced the neural network for linear program with linear constraints. In this paper, Hopfield neural network has been generalized to solve the optimization problems including nonlinear constraints. Also, it has been discussed the methods hew to reconcile optimization problem with neural networks and how to implement the circuits.

Nonlinear Response Structural Optimization of a Joined-Wing Using Equivalent Loads (등가하중법을 이용한 접합날개의 기하 비선형 응답 구조최적설계)

  • Kim, Yong-Il;Park, Gyung-Jin
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.321-326
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    • 2007
  • The joined-wing is a new concept of the airplane wing. The fore-wing and the aft-wing arc joined together in the joined-wing. The range and loiter are longer than those of a conventional wing. The joined-wing can lead to increased aerodynamic performances and reduction of the structural weight. The structural behavior of the joined-wing has a high geometric nonlinearity according to the external loads. The gust loads are the most critical loading conditions in the structural design of the joined-wing. The nonlinear behavior should be considered in the optimization of the joined-wing. It is well known that conventional nonlinear response optimization is extremely expensive: therefore, the conventional method is almost impossible to use in large scale structures such as the joined-wing. In this research, geometric nonlinear response structural optimization is carried out using equivalent loads. Equivalent loads are the load sets which generate the same response field in linear analysis as that from nonlinear analysis. In the equivalent loads method, 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.

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Unsupervised Endmember Selection Optimization Process based on Constrained Linear Spectral Unmixing of Hyperion Image (Hyperion 영상의 제약선형분광혼합분석 기반 무감독 Endmember 추출 최적화 기법)

  • Choi Jae-Wan;Kim Yong-Il;Yu Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.211-216
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    • 2006
  • The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

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A Face Optimization Algorithm for Optimizing over the Efficient Set

  • Kim, Dong-Yeop;Taeho Ahn
    • Korean Management Science Review
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    • v.15 no.1
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    • pp.77-85
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    • 1998
  • In this paper a face optimization algorithm is developed for solving the problem (P) of optimizing a linear function over the set of efficient solutions of a multiple objective linear program. Since the efficient set is in general a nonconvex set, problem (P) can be classified as a global optimization problem. Perhaps due to its inherent difficulty, relatively few attempts have been made to solve problem (P) in spite of the potential benefits which can be obtained by solving problem (P). The algorithm for solving problem (P) is guaranteed to find an exact optimal or almost exact optimal solution for the problem in a finite number of iterations.

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Shape Optimization of Structures with a Crack (균열이 있는 구조물의 형상 최적화)

  • 한석영;송시엽;백춘호
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2001.10a
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    • pp.298-303
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    • 2001
  • Most of mechanical failures are caused by repeated loadings and therefore they are strongly related to fatigue. To avoid the failures caused by fatigue, determination of an optimal shape of a structure is one of the very important factors in the initial design stage. Shape optimization for a compact tension specimen in opening mode in fracture mechanics, was accomplished by the linear elastic fracture mechanics and the growth-strain method in this study. Also shape optimization for a cantilever beam in mixed mode was carried out by the same techniques. The linear elastic fracture mechanics was used to estimate stress intensity factors and fatigue lives. And the growth-strain method was used to optimize the shape of the initial shape of the specimens. From the results of the shape optimization, it was found that shapes of two types of specimens and a cantilever beam optimized by the growth-strain method prolong their fatigue lives very much. Therefore, it was verified that the growth-strain method is an appropriate technique for shape optimization of a structure having a crack.

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Optimal design of double layer barrel vaults considering nonlinear behavior

  • Gholizadeh, Saeed;Gheyratmand, Changiz;Davoudi, Hamed
    • Structural Engineering and Mechanics
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    • v.58 no.6
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    • pp.1109-1126
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    • 2016
  • The present paper focuses on size optimization of double layer barrel vaults considering nonlinear behavior. In order to tackle the optimization problem an improved colliding bodies optimization (ICBO) algorithm is proposed. The important task that should be achieved before optimization of structural systems is to determine the best form having the least cost. In this study, an attempt is done to find the best form then it is optimized considering linear and non-linear behaviors. In the optimization process based on nonlinear behavior, the geometrical and material nonlinearity effects are included. A large-scale double layer barrel vault is presented as the numerical example of this study and the obtained results indicate that the proposed ICBO has better computational performance compared with other algorithms.