An exact penalty global optimization approach for mixed-integer programming problems
From MaRDI portal
Publication:1940438
DOI10.1007/s11590-011-0417-9zbMath1288.90054OpenAlexW1934729702MaRDI QIDQ1940438
Stefano Lucidi, Francesco Rinaldi
Publication date: 7 March 2013
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.725.7829
Related Items
Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates, Inversion of convection-diffusion equation with discrete sources, Improved penalty algorithm for mixed integer PDE constrained optimization problems, A trajectory-based method for mixed integer nonlinear programming problems, Firefly penalty-based algorithm for bound constrained mixed-integer nonlinear programming, An improved penalty algorithm using model order reduction for MIPDECO problems with partial observations
Cites Work
- Unnamed Item
- Unnamed Item
- An algorithm for nonlinear optimization problems with binary variables
- New results on the equivalence between zero-one programming and continuous concave programming
- Exact penalty functions for nonlinear integer programming problems
- Knapsack feasibility as an absolute value equation solvable by successive linear programming
- Penalty formulation for zero-one nonlinear programming
- Handbook of test problems in local and global optimization
- Lipschitzian optimization without the Lipschitz constant
- A polyhedral branch-and-cut approach to global optimization
- Convexification and global optimization in continuous and mixed-integer nonlinear programming. Theory, algorithms, software, and applications
- A partition-based global optimization algorithm
- Penalty for zero–one integer equivalent problem
- An exact penalty approach for solving a class of minimization problems with boolean variables
- On Connections Between Zero-One Integer Programming and Concave Programming Under Linear Constraints
- Constructing test functions for global optimization using continuous formulations of graph problems
- Introduction to global optimization.
- Finding independent sets in a graph using continuous multivariable polynomial formulations.
