A geometric characterization of "optimality-equivalent" relaxations
Journal of Global Optimization
Chebyshev center based column generation
Discrete Applied Mathematics
An in-out approach to disjunctive optimization
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
On the solution of a graph partitioning problem under capacity constraints
ISCO'12 Proceedings of the Second international conference on Combinatorial Optimization
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Most of integer, convex, and large-scale linear problems are solved using cutting plane and column generation algorithms. Therefore, to handle large-size problems and to reduce the computing times, it may be very useful to accelerate cutting plane algorithms. We show in this article that we can achieve this goal by choosing good separation points. Focus is given on problems for which we have an exact separation oracle. An in–out algorithm is proposed, and the convergence is proved under some general assumptions. Computational experiments related to three classes of problems, survivable network design, multicommodity flow problems, and random linear programs, clearly point out the savings of time allowed by the simple in–out approach proposed in this article. © 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 49(1), 3–17 2007