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tutorial:optimization [2014/05/27 08:10] – [Linear Optimization] paffenholz | user_guide:optimization [2019/01/25 09:27] – ↷ Page moved from tutorial:optimization to user_guide:optimization 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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=== 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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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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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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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< | ||
</ | </ |