Results 261 to 270 of about 26,851 (306)

Safe bounds in linear and mixed-integer linear programming

Mathematical Programming, 2004
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Arnold Neumaier, Oleg Shcherbina
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An optimality cut for mixed integer linear programs

European Journal of Operational Research, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gilbert Laporte, Frédéric Semet
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The Mixed Integer Linear Bilevel Programming Problem

Operations Research, 1990
A two-person, noncooperative game in which the players move in sequence can be modeled as a bilevel optimization problem. In this paper, we examine the case where each player tries to maximize the individual objective function over a jointly constrained polyhedron. The decision variables are variously partitioned into continuous and discrete sets. The
James T. Moore, Jonathan F. Bard
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Multiobjective Integer and Mixed-Integer Linear Programming

2016
The introduction of discrete variables into multiobjective programming problems leads to all-integer or mixed-integer problems that are more difficult to tackle, even if they have linear objective functions and constraints. The feasible set is no longer convex, and the additional difficulties go beyond those of changing from single objective linear ...
Carlos Henggeler Antunes, Maria João Alves, João Clímaco   +2 more
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From Mixed-Integer Linear to Mixed-Integer Bilevel Linear Programming

2017
Bilevel Optimization is a very challenging framework where two players (with different objectives) compete for the definition of the final solution. In this paper we address a generic mixed-integer bilevel linear program, i.e., a bilevel optimization problem where the objective functions and constraints are all linear, and some variables are required ...
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A DC Programming Approach for Mixed-Integer Linear Programs

2008
In this paper, we propose a new efficient algorithm for globally solving a class of Mixed Integer Program (MIP). If the objective function is linear with both continuous variables and integer variables, then the problem is called a Mixed Integer Linear Program (MILP). Researches on MILP are important in both theoretical and practical aspects.
Yi-Shuai Niu, Pham Dinh Tao
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Bivium as a Mixed-Integer Linear Programming Problem

2009
Trivium is a stream cipher proposed for the eSTREAM project. Raddum introduced some reduced versions of Trivium, named Bivium A and Bivium B. In this article we present a numerical attack on the Biviums. The main idea is to transform the problem of solving a sparse system of quadratic equations over GF (2) into a combinatorial optimization problem.
Julia Borghoff, Lars R. Knudsen, Mathias Stolpe   +2 more
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Guaranteed Outlier Removal with Mixed Integer Linear Programs

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
The maximum consensus problem is fundamentally important to robust geometric fitting in computer vision. Solving the problem exactly is computationally demanding, and the effort required increases rapidly with the problem size. Although randomized algorithms are much more efficient, the optimality of the solution is not guaranteed.
Tat-Jun Chin, Yang Heng Kee, Anders P. Eriksson, Frank Neumann 0001   +3 more
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Marginal values in mixed integer linear programming

Mathematical Programming, 1989
Marginal values of a given optimization problem are the directional partial derivatives of the value with respect to perturbations in the data. If \(v(c,A,b)=\min \{cx|\) Ax\(\geq b\), \(x\geq 0\}\) and if \(u=(c',A',b')\) is a vector, then the marginal value in direction u is defined by \[ \frac{\partial v}{\partial u}=\lim_{\epsilon \to 0+}\frac{v(c+\
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Linear and Mixed Integer Programming

2000
Linear Programming (LP) is one of the most famous optimization techniques introduced independently by Kantarowitsch in 1939 and by Dantzig in 1949 (Kreko, 1973). LP is applicable in decision situations where quantities (variables) can take any real values only restricted by linear (in-) equalities, e. g. for representing capacity constraints. Still, LP
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