10,231 research outputs found
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Developments in linear and integer programming
In this review we describe recent developments in linear and integer (linear) programming. For over 50 years Operational Research practitioners have made use of linear optimisation models to aid decision making and over this period the size of problems that can be solved has increased dramatically, the time required to solve problems has decreased substantially and the flexibility of modelling and solving systems has increased steadily. Large models are no longer confined to large computers, and the flexibility of optimisation systems embedded in other decision support tools has made on-line decision making using linear programming a reality (and using integer programming a possibility). The review focuses on recent developments in algorithms, software and applications and investigates some connections between linear optimisation and other technologies
Cutting plane methods for general integer programming
Integer programming (IP) problems are difficult to solve due to the integer restrictions imposed on them. A technique for solving these problems is the cutting plane method. In this method, linear constraints are added to the associated linear programming (LP) problem until an integer optimal solution is found. These constraints cut off part of the LP solution space but do not eliminate any feasible integer solution. In this report algorithms for solving IP due to Gomory and to Dantzig are presented. Two other cutting plane approaches and two extensions to Gomory's algorithm are also discussed. Although these methods are mathematically elegant they are known to have slow convergence and an explosive storage requirement. As a result cutting planes are generally not computationally successful
Branching on multi-aggregated variables
open5siopenGamrath, Gerald; Melchiori, Anna; Berthold, Timo; Gleixner, Ambros M.; Salvagnin, DomenicoGamrath, Gerald; Melchiori, Anna; Berthold, Timo; Gleixner, Ambros M.; Salvagnin, Domenic
The subdivision of large simplicial cones in Normaliz
Normaliz is an open-source software for the computation of lattice points in
rational polyhedra, or, in a different language, the solutions of linear
diophantine systems. The two main computational goals are (i) finding a system
of generators of the set of lattice points and (ii) counting elements
degree-wise in a generating function, the Hilbert Series. In the homogeneous
case, in which the polyhedron is a cone, the set of generators is the Hilbert
basis of the intersection of the cone and the lattice, an affine monoid.
We will present some improvements to the Normaliz algorithm by subdividing
simplicial cones with huge volumes. In the first approach the subdivision
points are found by integer programming techniques. For this purpose we
interface to the integer programming solver SCIP to our software. In the second
approach we try to find good subdivision points in an approximating overcone
that is faster to compute.Comment: To appear in the proceedings of the ICMS 2016, published by Springer
as Volume 9725 of Lecture Notes in Computer Science (LNCS
When Lift-and-Project Cuts are Different
In this paper, we present a method to determine if a lift-and-project cut for
a mixed-integer linear program is irregular, in which case the cut is not
equivalent to any intersection cut from the bases of the linear relaxation.
This is an important question due to the intense research activity for the past
decade on cuts from multiple rows of simplex tableau as well as on
lift-and-project cuts from non-split disjunctions. While it is known since
Balas and Perregaard (2003) that lift-and-project cuts from split disjunctions
are always equivalent to intersection cuts and consequently to such multi-row
cuts, Balas and Kis (2016) have recently shown that there is a necessary and
sufficient condition in the case of arbitrary disjunctions: a lift-and-project
cut is regular if, and only if, it corresponds to a regular basic solution of
the Cut Generating Linear Program (CGLP). This paper has four contributions.
First, we state a result that simplifies the verification of regularity for
basic CGLP solutions from Balas and Kis (2016). Second, we provide a
mixed-integer formulation that checks whether there is a regular CGLP solution
for a given cut that is regular in a broader sense, which also encompasses
irregular cuts that are implied by the regular cut closure. Third, we describe
a numerical procedure based on such formulation that identifies irregular
lift-and-project cuts. Finally, we use this method to evaluate how often
lift-and-project cuts from simple -branch split disjunctions are irregular,
and thus not equivalent to multi-row cuts, on 74 instances of the MIPLIB
benchmarks.Comment: INFORMS Journal on Computing (to appear
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Design, implementation and testing of an integrated branch and bound algorithm for piecewise linear and discrete programming problems within an LP framework
A number of discrete variable representations are well accepted and find regular use within LP systems. These are Binary variables, General Integer variables, Variable Upper Bounds or Semi Continuous variables, Special Ordered Sets of type One and type Two. The FortLP system has been extended to include these representations. A Branch and Bound algorithm is designed in which the choice of sub-problems and branching variables are kept general. This provides considerable scope of experimentation with tree development heuristics and the tree search can then be guided by search parameters specified by user subroutines. The data structures for representing the variables and the definition of the branch and bound tree are described. The results of experimental investigation for a few test problems are reported
Note on the Complexity of the Mixed-Integer Hull of a Polyhedron
We study the complexity of computing the mixed-integer hull
of a polyhedron .
Given an inequality description, with one integer variable, the mixed-integer
hull can have exponentially many vertices and facets in . For fixed,
we give an algorithm to find the mixed integer hull in polynomial time. Given
and fixed, we compute a vertex description of
the mixed-integer hull in polynomial time and give bounds on the number of
vertices of the mixed integer hull
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