The Semismooth Algorithm for Large Scale Complementarity Problems

Abstract

Complementarity solvers are continually being challenged by modelers demanding improved reliability and scalability. Building upon a strong theoretical background the semismooth algorithm has the potential to meet both of these requirements. We briefly discuss relevant theory associated with the algorithm and describe a sophisticated implementation in detail. Particular emphasis is given to robust methods for dealing with singularities in the linear system and to large scale issues. Results on the MCPLIB test suite indicate that the code is robust and has the potential to solve very large problems.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1999
Accession Number
ADA375452

Entities

People

  • Andreas Fischer
  • Christian Kanzow
  • Francisco Facchinei
  • Michael C. Ferris
  • Todd S. Munson

Organizations

  • University of Wisconsin Madison Department of Computer Science

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computations
  • Convergence
  • Equations
  • Errors
  • Iterations
  • Linear Algebra
  • Linear Systems
  • Nonlinear Dynamics
  • Nonlinear Programming
  • Nonlinear Systems
  • Numbers
  • Operations Research
  • Reliability
  • Sequences
  • Test Sets

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design