Modern homotopy methods in optimization
Computer Methods in Applied Mechanics and Engineering
Numerical continuation methods: an introduction
Numerical continuation methods: an introduction
Numerical analysis: mathematics of scientific computing
Numerical analysis: mathematics of scientific computing
Algorithm 777: HOMPACK90: a suite of Fortran 90 codes for globally convergent homotopy algorithms
ACM Transactions on Mathematical Software (TOMS)
LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
A Homotopy-Based Algorithm for Mixed Complementarity Problems
SIAM Journal on Optimization
A Probability-One Homotopy Algorithm for Nonsmooth Equations and Mixed Complementarity Problems
SIAM Journal on Optimization
Probability-one homotopies in computational science
Journal of Computational and Applied Mathematics - Special issue: Proceedings of the 9th International Congress on computational and applied mathematics
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Probability-one homotopy algorithms have strong convergence characteristics under mild assumptions. Such algorithms for mixed complementarity problems (MCPs) have potentially wide impact because MCPs are pervasive in science and engineering. A probability-one homotopy algorithm for MCPs was developed earlier by Billups and Watson based on the default homotopy mapping. This algorithm had guaranteed global convergence under some mild conditions, and was able to solve most of the MCPs from the MCPLIB test library. This paper extends that work by presenting some other homotopy mappings, enabling the solution of all the remaining problems from MCPLIB. The homotopy maps employed are the Newton homotopy and homotopy parameter embeddings.