
We introduce a concept that generalizes several different notions of a "centerpoint" in the literature. We develop an oracle-based algorithm for convex mixed-integer optimization based on centerpoints. Further, we show that algorithms based on centerpoints are "best possible" in a certain sense. Motivated by this, we establish several structural results about this concept and provide efficient algorithms for computing these points. Our main motivation is to understand the complexity of oracle based convex mixed-integer optimization.
Convex programming, Helly-type theorems and geometric transversal theory, Lattices and convex bodies in \(n\) dimensions (aspects of discrete geometry), convex mixed-integer optimization, convex and discrete geometry, Mixed integer programming, Optimization and Control (math.OC), FOS: Mathematics, centerpoints, 52A35, 52C07, 90C11, 90C25, QA, Mathematics - Optimization and Control
Convex programming, Helly-type theorems and geometric transversal theory, Lattices and convex bodies in \(n\) dimensions (aspects of discrete geometry), convex mixed-integer optimization, convex and discrete geometry, Mixed integer programming, Optimization and Control (math.OC), FOS: Mathematics, centerpoints, 52A35, 52C07, 90C11, 90C25, QA, Mathematics - Optimization and Control
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