International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Fuzzy-Enforced Complementarity Constraints in Nonlinear Interior Point Method-Based Optimization

  • Song, Hwachang (Department of Electrical and Information Engineering, Seoul National University of Science & Technology)
  • Received : 2013.05.31
  • Accepted : 2013.09.13
  • Published : 2013.09.25
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Abstract

This paper presents a fuzzy set method to enforce complementarity constraints (CCs) in a nonlinear interior point method (NIPM)-based optimization. NIPM is a Newton-type approach to nonlinear programming problems, but it adopts log-barrier functions to deal with the obstacle of managing inequality constraints. The fuzzy-enforcement method has been implemented for CCs, which can be incorporated in optimization problems for real-world applications. In this paper, numerical simulations that apply this method to power system optimal power flow problems are included.

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References

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