Abstract
This paper considers the problem of finding and verifying feasible points for constraint satisfaction problems (CSPs), including those with uncertain coefficients. The main part is devoted to the problem of finding a narrow box around an approximately feasible solution for which it can be rigorously and automatically proved that it contains a feasible solution. Some examples demonstrate difficulties when attempting verification. We review some existing methods and present a new method for verifying the existence of feasible points of CSPs in an automatically determined narrow box. Numerical tests within GloptLab, a solver developed by the authors, show how the different methods perform. Also discussed are the search for approximately feasible points and the use of approximately feasible points within a branch and bound scheme for constraint satisfaction.
Original language | English |
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Pages (from-to) | 255 - 278 |
Number of pages | 24 |
Journal | Journal of Global Optimization |
Volume | 61 |
Issue number | 2 |
Early online date | 4 Mar 2014 |
DOIs | |
Publication status | Published - Feb 2015 |
Austrian Fields of Science 2012
- 101016 Optimisation
Keywords
- Rigorous feasibility verification
- Constraint satisfaction
- Global optimization
- Verified computing
- Interval analysis