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A polyhedral branch-and-cut approach to global optimization

✍ Scribed by Mohit Tawarmalani; Nikolaos V. Sahinidis


Publisher
Springer-Verlag
Year
2005
Tongue
English
Weight
253 KB
Volume
103
Category
Article
ISSN
0025-5610

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We consider probabilistically constrained linear programs with general distributions for the uncertain parameters. These problems involve non-convex feasible sets. We develop a branch-and-bound algorithm that searches for a global optimal solution to this problem by successively partitioning the non