The Semismooth Algorithm for Large Scale Complementarity Problems

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Kanzow, Christian
Fischer, Andreas
Ferris, Michael
Facchinei, Francisco
Munson, Todd

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Technical Report

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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 descriptive a sophisticated implementation in detail. Particular emphasis is given to robust methods for dealing with singularities in 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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99-06

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