Lagrangian decomposition and mixed-integer quadratic programming reformulations for probabilistically constrained quadratic programs
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Publication:1926817
DOI10.1016/j.ejor.2012.03.006zbMath1253.90182OpenAlexW2050917173WikidataQ57445439 ScholiaQ57445439MaRDI QIDQ1926817
Xiaoling Sun, Xueting Cui, Li, Duan, Xiao Jin Zheng
Publication date: 29 December 2012
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2012.03.006
quadratic programmingprobabilistic constraintsemidefinite program relaxationmixed-integer quadratic program reformulationsecond-order cone programming relaxation
Related Items (8)
Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints ⋮ New reformulations for probabilistically constrained quadratic programs ⋮ A Lagrangian decomposition approach for the pump scheduling problem in water networks ⋮ An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems ⋮ A smooth non-parametric estimation framework for safety-first portfolio optimization ⋮ Cell-and-bound algorithm for chance constrained programs with discrete distributions ⋮ Quadratic convex reformulation for quadratic programming with linear on-off constraints ⋮ AN IMPROVED CONVEX 0-1 QUADRATIC PROGRAM REFORMULATION FOR CHANCE-CONSTRAINED QUADRATIC KNAPSACK PROBLEMS
Uses Software
Cites Work
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- A computational comparison of reformulations of the perspective relaxation: SOCP vs. cutting planes
- An integer programming approach for linear programs with probabilistic constraints
- Mathematical programming approaches for generating \(p\)-efficient points
- Convexity of chance constraints with independent random variables
- Relaxations for probabilistically constrained programs with discrete random variables
- Probabilistic programming with discrete distributions and precedence constrained knapsack polyhedra
- Uncertain convex programs: randomized solutions and confidence levels
- A heuristic algorithm for a chance constrained stochastic program
- A mixed integer linear programming formulation of the optimal mean/Value-at-Risk portfolio problem
- Perspective cuts for a class of convex 0-1 mixed integer programs
- A branch-reduce-cut algorithm for the global optimization of probabilistically constrained linear programs
- SDP diagonalizations and perspective cuts for a class of nonseparable MIQP
- Chance-Constrained Programming
- Solving Some Large Scale Semidefinite Programs via the Conjugate Residual Method
- Improving the Performance of MIQP Solvers for Quadratic Programs with Cardinality and Minimum Threshold Constraints: A Semidefinite Program Approach
- A Newton-CG Augmented Lagrangian Method for Semidefinite Programming
- An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints
- Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach
- Sharp Bounds on Probabilities Using Linear Programming
- An Efficient Trajectory Method for Probabilistic Production-Inventory-Distribution Problems
- The Probabilistic Set-Covering Problem
- Lectures on Stochastic Programming
- Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems
- A branch and bound method for stochastic integer problems under probabilistic constraints
- The Scenario Approach to Robust Control Design
- Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design
- Convex Approximations of Chance Constrained Programs
- Concavity and efficient points of discrete distributions in probabilistic programming.
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