A parallelized DPPQN based Expert System method and implementation

  • Authors:
  • Ch'i-Hsin Lin;Shieh-Shing Lin;Shih-Cheng Horng

  • Affiliations:
  • Department of Electronics Engineering, Kao Yuan University, Kaoshiung, Taiwan, ROC;Department of Electrical Engineering, St. John's University, 499, Sec. 4 Tam King Road, Tamsui, Taipei 25135, Taiwan, ROC;Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

In this paper, we propose a parallelized Dual Projected Pseudo Quasi-Newton (parallelized DPPQN) based Expert System method to solve a kind of distributed constrained optimization problem. The proposed parallelized DPPQN based Expert System method differs from the conventional Lagrange method by treating the inequality constraints as the domain of the original variable in the dual function and uses projection theory to process the inequality constraints. The proposed algorithm was implemented in a n+1 processors network. We also demonstrated the efficiency in solving a typical constrained weighted least squares problem in power system. The parallelized DPPQN based Expert System method associated with a projected Jacobi method can be applied to general large scale nonlinear network optimization problems in large distributed interconnected systems.