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2011
We describe and survey the main component and the usage of Mixed-Integer Linear Programming Solvers.
J. T. Linderoth, LODI, ANDREA
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We describe and survey the main component and the usage of Mixed-Integer Linear Programming Solvers.
J. T. Linderoth, LODI, ANDREA
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MILP Formulation for Energy Mix Optimization
IEEE Transactions on Industrial Informatics, 2015Energy mix (EM) is a term used to describe a share of different technologies used to meet the demand for electric power and energy. Development of EM is driven by many factors such as economic constraints, technical constraints, environmental requirements, and policy aspects.
Wojciech Lyzwa +2 more
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Fast MILP Modelings for Sboxes
2021 4th International Conference on Computer Science and Software Engineering (CSSE 2021), 2021Hao Tan +3 more
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Accelerated MILP-Strategies for the Optimal
2003In this paper a MILP-based opt imization algorithm for the optimaloperation planning of energy supply systems is presented. For this purpose, the maintasks of optimal operation planning are discussed and th e Priority-Based DynamicSearch Strategy (PBDSS) for the solution of the optimization problem is developed taking into account different ...
Peter Häcklander, Johannes F. Verstege
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Global Optimisation of mp-MILP Problems
2009Abstract In this paper a novel global optimisation approach is introduced for solving multiparametric Mixed Integer Linear Programs (mp-MILP), with varying parameters in the objective function and the right-hand side of the constraints. The mp-MILP problem is decomposed into two sub-problems, a Master MINLP problem and a Slave multiparametric global ...
Nuno P. Faísca +2 more
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Multi-Group Data Classification via MILP
2009Data classification is a supervised learning strategy that analyzes the organization and categorization of data in distinct classes. Generally, a training set, in which all objects are already associated with known class labels, is used in classification methods. The data classification algorithms work on this set by using input attributes and builds a
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Solving Nonlinear Problems with MILP Models
2009Although the author is an Electrical Engineer he got interested in optimization problems using the GAMS software. Rapidly he understood the limitations of the nonlinear solvers, like the necessity to have an initial feasible solution and the high probability of the solver being trapped in a local optimum and since 2004 he solved a set of complex ...
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