Optimal training of integer-valued neural networks with mixed integer programming [PDF]
PLoS ONE, 2023 Recent work has shown potential in using Mixed Integer Programming (MIP) solvers to optimize certain aspects of neural networks (NNs). However the intriguing approach of training NNs with MIP solvers is under-explored.
Tómas Thorbjarnarson, Neil Yorke-Smith
doaj +3 more sources
A parametric integer programming algorithm for bilevel mixed integer programs [PDF]
Journal of Optimization Theory and Applications, 2009 We consider discrete bilevel optimization problems where the follower solves an integer program with a fixed number of variables. Using recent results in parametric integer programming, we present polynomial time algorithms for pure and mixed integer ...
A. Barvinok +23 more
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Multistage Distributionally Robust Mixed-Integer Programming with Decision-Dependent Moment-Based Ambiguity Sets [PDF]
Mathematical programming, 2020 We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisions made in previous stages.
Xian Yu, Siqian Shen
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A mixed-integer linear programming approach for robust state estimation [PDF]
Journal of Modern Power Systems and Clean Energy, 2014 In this paper, a mixed integer linear programming (MILP) formulation for robust state estimation (RSE) is proposed. By using the exactly linearized measurement equations instead of the original nonlinear ones, the existing mixed integer nonlinear ...
Yanbo Chen, Jin Ma
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Comparative Network Reconstruction using mixed integer programming. [PDF]
Bioinformatics, 2018 Abstract Motivation Signal-transduction networks are often aberrated in cancer cells, and new anti-cancer drugs that specifically target oncogenes involved in signaling show great clinical promise.
Bosdriesz E +7 more
europepmc +6 more sources
Mixed Integer Linear Programming Formulation Techniques [PDF]
SIAM Review, 2014 A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP) problems using standard formulation techniques. However, in some cases the resulting MIP can be either too weak or too large to be effectively solved by state of the art ...
Vielma, Juan Pablo
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Computational load reduction of the agent guidance problem using Mixed Integer Programming. [PDF]
PLoS One, 2020 Battagello VA, Soma NY, Afonso RJM.
europepmc +3 more sources
Mixed-integer nonlinear programming 2018 [PDF]
Optimization and Engineering, 2019 Mixed-Integer Nonlinear Programming (MINLP) is the area of optimization that addresses nonlinear problems with continuous and integer variables. MINLP has proven to be a powerful tool for modeling. At the same time, it combines algorithmic design challenges from combinatorial and nonlinear optimization.
N. Sahinidis
semanticscholar +2 more sources
On Mixed-Integer Random Convex Programs [PDF]
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012 We consider a class of mixed-integer optimization problems subject to N randomly drawn convex constraints. We provide explicit bounds on the tails of the probability that the optimal solution found under these N constraints will become infeasible for the next random constraint.
Giuseppe C. Calafiore +2 more
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A multi-objective multi-period mathematical programming model for integrated project portfolio optimization and contractor selection [PDF]
MethodsXThis paper addresses the challenges of project portfolio optimization and contractor selection through two proposed scenarios. In the first scenario, two separate mixed-integer mathematical programming models are presented: one for project portfolio ...
Mostafa Zahedirad +3 more
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