Improving branch-and-cut performance by random sampling
نویسندگان
چکیده
We discuss the variability in the performance of multiple runs of branchand-cut mixed integer linear programming solvers, and we concentrate on the one deriving from the use of different optimal bases of the linear programming relaxations. We propose a new algorithm exploiting more than one of those bases and we show that different versions of the algorithmcanbeused to stabilize and improve the performance of the solver.
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عنوان ژورنال:
- Math. Program. Comput.
دوره 8 شماره
صفحات -
تاریخ انتشار 2016