Results 71 to 80 of about 47,013 (110)
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Mixed-integer Nonlinear Optimization: a hatchery for modern mathematics
Oberwolfach Reports, 2020The second MFO Oberwolfach Workshop on Mixed-Integer Nonlinear Programming (MINLP) took place between 2nd and 8th June 2019. MINLP refers to one of the hardest Mathematical Programming (MP) problem classes, involving both nonlinear functions as well as ...
Leo Liberti +2 more
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An approximation algorithm for indefinite mixed integer quadratic programming
Mathematical programming, 2022In this paper, we give an algorithm that finds an ϵ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}
Alberto Del Pia
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Presolve Reductions in Mixed Integer Programming
INFORMS journal on computing, 2020Mixed integer programming has become a very powerful tool for modeling and solving real-world planning and scheduling problems, with the breadth of applications appearing to be almost unlimited. A critical component in the solution of these mixed integer
Tobias Achterberg +4 more
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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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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 Criterion Space Method for Biobjective Mixed Integer Programming: The Boxed Line Method
INFORMS journal on computing, 2020Despite recent interest in multiobjective integer programming, few algorithms exist for solving biobjective mixed integer programs. We present such an algorithm: the boxed line method.
Tyler A. Perini +3 more
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Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming
Mathematical programmingMixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. The main engine for solving MILPs is the branch-and-bound algorithm.
Lara Scavuzzo +3 more
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Strong mixed-integer programming formulations for trained neural networks
Mathematical programming, 2018We present strong mixed-integer programming (MIP) formulations for high-dimensional piecewise linear functions that correspond to trained neural networks.
Ross Anderson +4 more
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Analyzing the Numerical Correctness of Branch-and-Bound Decisions for Mixed-Integer Programming
Integration of AI and OR Techniques in Constraint ProgrammingMost state-of-the-art branch-and-bound solvers for mixed-integer linear programming rely on limited-precision floating-point arithmetic and use numerical tolerances when reasoning about feasibility and optimality during their search.
Alexander Hoen, Ambros M. Gleixner
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A mixed integer programming approach to the tensor complementarity problem
Journal of Global Optimization, 2018The tensor complementarity problem is a special instance of nonlinear complementarity problems, which has many applications. How to solve the tensor complementarity problem, via analyzing the structure of the related tensor, is one of very important ...
S. Du, Liping Zhang
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Multi-objective mixed integer programming and an application in a pharmaceutical supply chain
International Journal of Production Research, 2018Multi-objective integer linear and/or mixed integer linear programming (MOILP/MOMILP) are very useful for many areas of application as any model that incorporates discrete phenomena requires the consideration of integer variables.
S. Singh, M. Goh
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