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tutorial:optimization [2013/08/26 15:52] – pfetsch | user_guide:tutorials:optimization [2019/01/25 10:56] – ↷ Links adapted because of a move operation oroehrig | ||
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There are several other tutorials that cover similar topics: | There are several other tutorials that cover similar topics: | ||
- | * [[tutorial: | + | * [[user_guide: |
- | * [[tutorial: | + | * [[user_guide: |
- | * [[tutorial: | + | * [[user_guide: |
- | * [[tutorial: | + | * [[user_guide: |
This tutorial is targeted towards the optimization community, since, surprisingly, | This tutorial is targeted towards the optimization community, since, surprisingly, | ||
+ | You can find files of the example LPs in the folder '' | ||
===== Input: lp2poly ===== | ===== Input: lp2poly ===== | ||
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</ | </ | ||
- | Thus, the file describes a 0/1-cube in three dimensions. It should be easy to adapt this format to other cases (If for example '' | + | Thus, the file describes a 0/1-cube in three dimensions. It should be easy to adapt this format to other cases (If for example '' |
- | + | ||
- | Now assume that this example is contained in file '' | + | |
< | < | ||
- | polytope > $f=lp2poly(' | + | polytope > $f=lp2poly(' |
</ | </ | ||
The polytope '' | The polytope '' | ||
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1 0 1 1 | 1 0 1 1 | ||
</ | </ | ||
- | This vertex corresponds to setting '' | + | This vertex corresponds to setting '' |
< | < | ||
polytope > print $p-> | polytope > print $p-> | ||
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polytope > $p-> | polytope > $p-> | ||
</ | </ | ||
- | {{ :tutorial: | + | {{ user_guide: |
The minimal and maximal faces can be visualized via | The minimal and maximal faces can be visualized via | ||
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polytope > $p-> | polytope > $p-> | ||
</ | </ | ||
- | {{ :tutorial: | + | {{ user_guide: |
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=== Bounded Polyhedra === | === Bounded Polyhedra === | ||
- | Let us illustrate the approach via the example of the //stable set problem//: Here one is given an (undirected) Graph G = (V,E) with node set V and edges E. The goal is to find a largest subset of node V' such that any two nodes in V' are not connected by an edge. | + | Let us illustrate the approach via the example of the //stable set problem//: Here one is given an (undirected) Graph G = (V,E) with node set V and edges E. The goal is to find a largest subset of nodes V' such that any two nodes in V' are not connected by an edge. |
For our example consider the 5-cycle, i.e., the graph C< | For our example consider the 5-cycle, i.e., the graph C< | ||
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We assume that the above information is contained in the file '' | We assume that the above information is contained in the file '' | ||
< | < | ||
- | polytope > $f=lp2poly(' | + | polytope > $f=lp2poly(' |
polytope > $p = new Polytope< | polytope > $p = new Polytope< | ||
</ | </ | ||
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End | End | ||
</ | </ | ||
- | {{ :tutorial: | + | {{ user_guide: |
We now assume that the example is contained in the file '' | We now assume that the example is contained in the file '' | ||
< | < | ||
- | polytope > $f = lp2poly(' | + | polytope > $f = lp2poly(' |
polytope > $pin = new Polytope< | polytope > $pin = new Polytope< | ||
</ | </ | ||
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</ | </ | ||
- | {{ :tutorial: | + | {{ user_guide: |
Note that the upper right part (including the red vertices) arises from truncation of the polyhedron for visualization. | Note that the upper right part (including the red vertices) arises from truncation of the polyhedron for visualization. | ||
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In this example there are two integral variables '' | In this example there are two integral variables '' | ||
< | < | ||
- | polytope > $m=lp2poly(' | + | polytope > $m=lp2poly(' |
polytope > $p = new Polytope< | polytope > $p = new Polytope< | ||
</ | </ | ||
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===== Integral Polytopes and Total Unimodularity ===== | ===== Integral Polytopes and Total Unimodularity ===== | ||
- | As explained in the previous example, the integral points in a polytope are of particular interest in discrete optimization. These points are called //lattice points// in polymake and the corresponding convex hull //lattice polytope//. The handling of such polytopes is explained in more detail in the [[tutorial: | + | As explained in the previous example, the integral points in a polytope are of particular interest in discrete optimization. These points are called //lattice points// in polymake and the corresponding convex hull //lattice polytope//. The handling of such polytopes is explained in more detail in the [[user_guide: |
Of particular interest for discrete optimization are properties of the orginal inequality system to define a lattice polytope, i.e., a polytope such that all of its vertices are integral (this can be tested by checking the property '' | Of particular interest for discrete optimization are properties of the orginal inequality system to define a lattice polytope, i.e., a polytope such that all of its vertices are integral (this can be tested by checking the property '' | ||
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In the second example, we reuse the file '' | In the second example, we reuse the file '' | ||
< | < | ||
- | polytope > $f=lp2poly(' | + | polytope > $f=lp2poly(' |
polytope > $p = new Polytope< | polytope > $p = new Polytope< | ||
</ | </ | ||
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Let us test whether the inequality system of this example is TDI. Thus, we first load the data as usual: | Let us test whether the inequality system of this example is TDI. Thus, we first load the data as usual: | ||
< | < | ||
- | polytope > $f = lp2poly(' | + | polytope > $f = lp2poly(' |
polytope > $p = new Polytope< | polytope > $p = new Polytope< | ||
</ | </ | ||
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*Note* that we need to take the inequalities instead of facets here, since facets are irredundant and thus might not be TDI, although the complete set of inequalities is TDI. | *Note* that we need to take the inequalities instead of facets here, since facets are irredundant and thus might not be TDI, although the complete set of inequalities is TDI. | ||
- | ===== 0/ | ||
===== Chvátal-Gomory Closure ===== | ===== Chvátal-Gomory Closure ===== | ||
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As before we read in the file using '' | As before we read in the file using '' | ||
< | < | ||
- | polytope > $f = lp2poly(' | + | polytope > $f = lp2poly(' |
polytope > $p = new Polytope< | polytope > $p = new Polytope< | ||
</ | </ | ||
- | The Chvátal-Gomory closure of a polytope can be computed with the function '' | + | The Chvátal-Gomory closure of a polytope can be computed with the function '' |
< | < | ||
polytope > $g = gc_closure($p); | polytope > $g = gc_closure($p); | ||
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==== Chvátal-Gomory Closure - Example 2 ==== | ==== Chvátal-Gomory Closure - Example 2 ==== | ||
- | Let us now consider the classical example of a polytope with the vertices of simplex in d dimensions and the point 1/2 times (1, ..., 1). It can be shown that such a polytope has rank at least log(d) - 1, see [Pokutta, 2011]. In our example, we use d = 4: | + | Let us now consider the classical example of a polytope with the vertices of simplex in d dimensions and the point 1/2 times (1, ..., 1). It can be shown that such a polytope has rank at least log(d) - 1, see [[http:// |
< | < | ||
polytope > $M = new Matrix< | polytope > $M = new Matrix< | ||
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===== Lift-and-project closure ===== | ===== Lift-and-project closure ===== | ||
- | ===== Other Software | + | The lift-and-project closure of a 0/ |
+ | < | ||
+ | sub lpclosure | ||
+ | { | ||
+ | my $p = shift; | ||
+ | my $d = $p-> | ||
+ | my $q = new Polytope< | ||
+ | for (my $k = 0; $k < $d; $k = $k+1) | ||
+ | { | ||
+ | if ( $q-> | ||
+ | { | ||
+ | return $q; | ||
+ | } | ||
+ | |||
+ | # create reversed opposite inequalities of 0/1-cube and corresponding polyhedra | ||
+ | my $v1 = new Vector< | ||
+ | my $v2 = new Vector< | ||
+ | |||
+ | # create intersection of corresponding polyhedra with iterated polyhedron $q | ||
+ | my $b1 = new Polytope< | ||
+ | my $b2 = new Polytope< | ||
+ | |||
+ | if ( ($b1-> | ||
+ | { | ||
+ | my $c = conv($b1, $b2); | ||
+ | $q = intersection($q, | ||
+ | } | ||
+ | elsif ( ($b1-> | ||
+ | { | ||
+ | $q = intersection($q, | ||
+ | } | ||
+ | elsif ( ($b1-> | ||
+ | { | ||
+ | $q = intersection($q, | ||
+ | } | ||
+ | } | ||
+ | | ||
+ | } | ||
+ | </ | ||
+ | |||
+ | ==== Lift-and-Projet Closure - Example 1 ==== | ||
+ | |||
+ | For our well known stable set example, we get the following: | ||
+ | < | ||
+ | polytope > $q = lpclosure($p); | ||
+ | polytope > $q-> | ||
+ | polytope > print_constraints($q); | ||
+ | Facets: | ||
+ | 0: -x4 - x5 >= -1 | ||
+ | 1: -x2 - x3 >= -1 | ||
+ | 2: -x1 - x2 - x3 - x4 - x5 >= -2 | ||
+ | 3: -x1 - x5 >= -1 | ||
+ | 4: -x3 - x4 >= -1 | ||
+ | 5: x2 >= 0 | ||
+ | 6: x1 >= 0 | ||
+ | 7: x3 >= 0 | ||
+ | 8: -x1 - x2 >= -1 | ||
+ | 9: x4 >= 0 | ||
+ | 10: x5 >= 0 | ||
+ | </ | ||
+ | Thus, the lift-and-project closure in this case gives the integral hull (as we have seen above). | ||
+ | |||
+ | ==== Lift-and-Projet Closure - Example 2 ==== | ||
+ | |||
+ | Let us now consider the same example as for CG-closures: | ||
+ | < | ||
+ | polytope > $M = new Matrix< | ||
+ | polytope > $p = new Polytope< | ||
+ | polytope > $q = lpclosure($p); | ||
+ | polytope > $q-> | ||
+ | polytope > print_constraints($q); | ||
+ | Facets: | ||
+ | 0: x2 >= 0 | ||
+ | 1: x4 >= 0 | ||
+ | 2: -x1 - x2 - x3 - x4 >= -1 | ||
+ | 3: x3 >= 0 | ||
+ | 4: x1 >= 0 | ||
+ | </ | ||
+ | Thus, we have obtained the integral hull in a single step of the lift-and-project closure as opposed to two steps in the CG-closure. | ||