An Integer Programming and Decomposition Approach to General Chance-Constrained Mathematical Programs
From MaRDI portal
Publication:3569824
DOI10.1007/978-3-642-13036-6_21zbMath1285.90024OpenAlexW1812936472MaRDI QIDQ3569824
Publication date: 22 June 2010
Published in: Integer Programming and Combinatorial Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-642-13036-6_21
Related Items (18)
A discussion of probability functions and constraints from a variational perspective ⋮ On the Quantile Cut Closure of Chance-Constrained Problems ⋮ The Minimum Spanning k-Core Problem with Bounded CVaR Under Probabilistic Edge Failures ⋮ A comparison of four approaches from stochastic programming for large-scale unit-commitment ⋮ Chance-Constrained Binary Packing Problems ⋮ Covering Linear Programming with Violations ⋮ Derivatives of probability functions: unions of polyhedra and elliptical distributions ⋮ A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support ⋮ An exact algorithm for the maximum probabilistic clique problem ⋮ Mixed integer linear programming formulations for probabilistic constraints ⋮ On the Convexity of Level-sets of Probability Functions ⋮ Sharp upper and lower bounds for maximum likelihood solutions to random Gaussian bilateral inequality systems ⋮ On the chance-constrained minimum spanning \(k\)-core problem ⋮ A cutting plane method for risk-constrained traveling salesman problem with random arc costs ⋮ Branch-and-cut approaches for chance-constrained formulations of reliable network design problems ⋮ Generalized Differentiation of Probability Functions Acting on an Infinite System of Constraints ⋮ Generalized differentiation of probability functions: parameter dependent sets given by intersections of convex sets and complements of convex sets ⋮ A linear programming approach for linear programs with probabilistic constraints
This page was built for publication: An Integer Programming and Decomposition Approach to General Chance-Constrained Mathematical Programs
