Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints
博士 === 國立交通大學 === 電機與控制工程系 === 90 === First of all, we present a modified parallel block scaled gradient method for solving block additive unconstrained optimization problems of large distributed systems. Our method makes two major modifications on the typical parallel block scaled gradie...
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ndltd-TW-090NCTU05910992015-10-13T10:08:07Z http://ndltd.ncl.edu.tw/handle/45081152549082892331 Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints 具非集總步幅之修正式平行區域比例梯度法及具耦合不等式限制之非線性大型網路最佳化問題的解法 Lin Shieh-Shing 林謝興 博士 國立交通大學 電機與控制工程系 90 First of all, we present a modified parallel block scaled gradient method for solving block additive unconstrained optimization problems of large distributed systems. Our method makes two major modifications on the typical parallel block scaled gradient method: (1) we include a pre-processing step which will reduce the computation time; (2) we present a decentralized Armijo-type step-size rule. This rule will circumvent the difficulty of determining a step-size in a distributed computing environment and enable the proposed parallel algorighm to execute in a distributed computer network with limited amount of data transfer. We prove that method is globally convergent and demonstrate its efficiency comparted to a sparse matrix technique based method by several weighted least square problems of power system state estimation. Secondly, with the decentralized step-size rule technique. We present a parallel dual-type algorithm for solving a class of quadratic programming problem. Our algorithm is suitable for implementation in a distributed computer network and can be used as a basic optimization tool for handling optimization problems of large distributed system. Finally, we present two new techniques for solving optimal power flow (OPF) problem with large number of thermal-limit constraints. The first one is a graph method based decomposition technique which can decompose the large-dimension projection problem, caused by the large number of thermal-limit constraints, into several independent medium-dimension projection subproblems at the expense of slight increment of the dual problem’s dimension. The second technique is an active-set strategy based DT method, which can solve the medium-dimension projection subproblems efficiently. We have used the DT method embedded with these two new techniques in solving numerous OPFs with large number of thermal-limit constraints. The test results show that the proposed techniques are very efficient and effectively improve the DT method for handling large number of thermal-limit constraints. Lin Shin-Yeu 林心宇 2002 學位論文 ; thesis 71 zh-TW |
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博士 === 國立交通大學 === 電機與控制工程系 === 90 === First of all, we present a modified parallel block scaled gradient method for solving block additive unconstrained optimization problems of large distributed systems. Our method makes two major modifications on the typical parallel block scaled gradient method: (1) we include a pre-processing step which will reduce the computation time; (2) we present a decentralized Armijo-type step-size rule. This rule will circumvent the difficulty of determining a step-size in a distributed computing environment and enable the proposed parallel algorighm to execute in a distributed computer network with limited amount of data transfer. We prove that method is globally convergent and demonstrate its efficiency comparted to a sparse matrix technique based method by several weighted least square problems of power system state estimation.
Secondly, with the decentralized step-size rule technique. We present a parallel dual-type algorithm for solving a class of quadratic programming problem. Our algorithm is suitable for implementation in a distributed computer network and can be used as a basic optimization tool for handling optimization problems of large distributed system.
Finally, we present two new techniques for solving optimal power flow (OPF) problem with large number of thermal-limit constraints. The first one is a graph method based decomposition technique which can decompose the large-dimension projection problem, caused by the large number of thermal-limit constraints, into several independent medium-dimension projection subproblems at the expense of slight increment of the dual problem’s dimension. The second technique is an active-set strategy based DT method, which can solve the medium-dimension projection subproblems efficiently. We have used the DT method embedded with these two new techniques in solving numerous OPFs with large number of thermal-limit constraints. The test results show that the proposed techniques are very efficient and effectively improve the DT method for handling large number of thermal-limit constraints.
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author2 |
Lin Shin-Yeu |
author_facet |
Lin Shin-Yeu Lin Shieh-Shing 林謝興 |
author |
Lin Shieh-Shing 林謝興 |
spellingShingle |
Lin Shieh-Shing 林謝興 Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
author_sort |
Lin Shieh-Shing |
title |
Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
title_short |
Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
title_full |
Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
title_fullStr |
Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
title_full_unstemmed |
Methods for Modified Parallel Block Scaled Gradient with Decentralized Step-size and Nonlinear Large Network Optimization Problem with Coupling Inequality Constraints |
title_sort |
methods for modified parallel block scaled gradient with decentralized step-size and nonlinear large network optimization problem with coupling inequality constraints |
publishDate |
2002 |
url |
http://ndltd.ncl.edu.tw/handle/45081152549082892331 |
work_keys_str_mv |
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