Pseudo basic steps: bound improvement guarantees from Lagrangian decomposition in convex disjunctive programming
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Publication:1742902
DOI10.1007/s13675-017-0088-0zbMath1390.90401OpenAlexW2737166611MaRDI QIDQ1742902
Dimitri J. Papageorgiou, Francisco Trespalacios
Publication date: 12 April 2018
Published in: EURO Journal on Computational Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13675-017-0088-0
disjunctive programmingLagrangian decomposition\(K\)-means clusteringbasic stepmixed-integer conic quadratic optimization
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- Lagrangean relaxation of the hull-reformulation of linear generalized disjunctive programs and its use in disjunctive branch and bound
- A hierarchy of relaxations for linear generalized disjunctive programming
- A hierarchy of relaxations for nonlinear convex generalized disjunctive programming
- Modeling disjunctive constraints with a logarithmic number of binary variables and constraints
- Disjunctive programming: Properties of the convex hull of feasible points
- Lagrangean relaxation. (With comments and rejoinder).
- Branching rules revisited
- A branch-and-cut method for 0-1 mixed convex programming
- Convex programming for disjunctive convex optimization
- On mathematical programming with indicator constraints
- A lift-and-project cutting plane algorithm for mixed 0-1 programs
- On handling indicator constraints in mixed integer programming
- Lectures on Modern Convex Optimization
- Algorithmic Approach for Improved Mixed-Integer Reformulations of Convex Generalized Disjunctive Programs
- Disjunctive Programming
- Disjunctive Programming and a Hierarchy of Relaxations for Discrete Optimization Problems
- Disjunctive Programming
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