標題: A parallel block scaled gradient method with decentralized step-size for block additive unconstrained optimization problems of large distributed systems
作者: Lin, SY
Lin, SS
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: unconstrained optimization;nonlinear programming;parallel computation;large distributed systems;least-square problems
公開日期: 1-Mar-2003
摘要: In this paper, we propose a modified parallel block scaled gradient method for solving block additive unconstrained optimization problems of large distributed systems. Our method makes two major modifications to the typical parallel block scaled gradient method: First, we include a pre-processing step which reduces the computational time; second, we propose a decentralized Armijo-type step-size rule. This rule circumvents the difficulty of determining a step-size in a distributed computing environment and enables the proposed parallel algorithm to execute in a distributed computer network with a limited amount of data transfer. We have applied our method to the weighted-least-square problems of power system state estimation and demonstrated the convergence of our method by testing numerous examples on a PC network. The speedup ratio of the distributed version of our method tends to increase proportionally with the number of subsystems (or computers).
URI: http://hdl.handle.net/11536/28073
ISSN: 1561-8625
期刊: ASIAN JOURNAL OF CONTROL
Volume: 5
Issue: 1
起始頁: 104
結束頁: 115
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