Abstract
This paper provides a means for comparing various computer codes for solving large scale mixed complementarity problems. We discuss inadequacies in how solvers are currently compared, and present a testing environment that addresses these inadequacies. This testing environment consists of a library of test problems, along with GAMS and MATLAB interfaces that allow these problems to be easily accessed. The environment is intended for use as a tool by other researchers to better understand both their algorithms and their implementations, and to direct research toward problem classes that are currently the most challenging. As an initial benchmark, eight different algorithm implementations for large scale mixed complementarity problems are briefly described and tested with default parameter settings using the new testing environment.
This material is based on research supported by National Science Foundation Grant CCR-9157632 and the Air Force Office of Scientific Research Grant F49620-94-1-0036.
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© 1997 Kluwer Academic Publishers, Boston
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Billups, S.C., Dirkse, S.P., Ferris, M.C. (1997). A Comparison of Large Scale Mixed Complementarity Problem Solvers. In: Murli, A., Toraldo, G. (eds) Computational Issues in High Performance Software for Nonlinear Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-26778-4_2
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DOI: https://doi.org/10.1007/978-0-585-26778-4_2
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