Mixed-integer nonlinear optimization*†

By Pietro Belotti, Christian Kirches, Sven Leyffer, Jeff T. Linderoth, James R. Luedtke, Ashutosh Mahajan. 2013

764 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Numerical Analysis

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Citations in the corpus

Benchmark and Survey of Automated Machine Learning Frameworks (2019, background): “As hyperparameters can be categorical and real-valued, Equation (2) is a mixed-integer nonlinear optimization problem (Belotti et al., 2013). Furthermore, conditional dependencies between different hyperparameters exist. If for example the ith algorithm is selected only Λ(i) is relevant as all other”
Survey on Automated Machine Learning (2019, background): “ation (2) is not easily solvable as the search space is quite large and complex. As hyperparameters can be categorical and real-valued, Equation (2) is a mixed-integer nonlinear optimization problem (Belotti et al., 2013). Furthermore, conditional dependencies between dierent hyperparameters exist. ”
Polyhedral approximation in mixed-integer convex optimization (2016, background): “Hence, despite numerous potential applications (see the reviews [5,10]), our perception is that MICP has not entered the mainstream of optimization techniques, perhaps with the exception of the special case of mixed-integer second-order cone programming (MISOCP) which we will discuss at length.”
A disjunctive convex programming approach to the pollution-routing problem (2016, methodology): “For an overview of the latest algorithmic developments and available solvers for the MICP, we refer the readers to a recent survey (Belotti et al. 2013) and the book (Lee and Leyffer 2012).”
ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations (2014, background): “…applicable in diverse domains ranging from molecular biology to reﬁnery operations to computational chemistry to synthesizing sustainable processes [16,24,50–53,63 , 64 , This manuscript presents ANTIGONE (Algorithms for coNTinuous/Integer Global Optimization of Nonlinear Equations; ﬁrst available…”
Energy management system for smart grid: An overview and key issues (2020, methodology): “When the system is subjected to dynamics with discrete decisions variables and nonlinearity, MINLP is helpful to find an optimal solution that combines the function of NLP and MILP (as subproblem).(189) Table 9 provides a comparative analysis of different programming method used for achieving an opt”