Tightening discretization-based MILP models for the pooling problem using upper bounds on bilinear terms
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Publication:6181371
DOI10.1007/s11590-023-01985-yarXiv2207.03699MaRDI QIDQ6181371
Xiaomin Zhang, Christos T. Maravelias, Yifu Chen
Publication date: 22 January 2024
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2207.03699
Cites Work
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- Global optimization of bilinear programs with a multiparametric disaggregation technique
- Relaxations and discretizations for the pooling problem
- New multi-commodity flow formulations for the pooling problem
- Global minimization by reducing the duality gap
- Convexification and global optimization in continuous and mixed-integer nonlinear programming. Theory, algorithms, software, and applications
- Solving pooling problems with time discretization by LP and SOCP relaxations and rescheduling methods
- Convex hull representations for bounded products of variables
- Convexifications of rank-one-based substructures in QCQPs and applications to the pooling problem
- Preprocessing algorithm and tightening constraints for multiperiod blend scheduling: cost minimization
- An adaptive, multivariate partitioning algorithm for global optimization of nonconvex programs
- QPLIB: a library of quadratic programming instances
- Strong formulations for the pooling problem
- Solving Mixed Integer Bilinear Problems Using MILP Formulations
- Valid Inequalities for the Pooling Problem with Binary Variables
- Analysis of MILP Techniques for the Pooling Problem
- Aggregation and Mixed Integer Rounding to Solve MIPs
- Strong Convex Nonlinear Relaxations of the Pooling Problem
- Benchmarking optimization software with performance profiles.
- The computational complexity of the pooling problem
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