Are you looking for something like the below that finds the subset of nodes
being used?
set nodes := {"A", "B", "C", "D", "E"};
set arcs within nodes cross nodes := {("A","B"), ("B","E")};
display nodes;
display arcs;
set nodes_that_are_used :=
setof{tail_node in nodes, head_node in nodes : (tail_node, head_node) in arcs
} tail_node
union
setof{tail_node in nodes, head_node in nodes : (tail_node, head_node) in arcs
} head_node;
display nodes_that_are_used;
end;
From: [email protected]
[mailto:[email protected]] On Behalf Of
Abhishek Shivakumar
Sent: Thursday, March 31, 2016 9:18 AM
To: [email protected]
Subject: [Help-glpk] Condensing a sparse matrix by creating a subset of
parameter data
Hi,
I have an lp model that produces an extremely sparse constraint matrix. I would
like to reduce the number of non-zero entries in this matrix (make the matrix
more dense). The main cause of this sparse-ness is the relation between two
parameters. They can be seen as 'arcs' and 'nodes: not all nodes have arcs
between them. Is there a way to create a subset of parameter data from the sets
'arcs' and 'nodes' based on whether they are connected? I would then be able to
apply constraints only for this subset. In other languages (such as python)
such an operation is possible through nested conditional statements. Is there a
similar/equivalent approach in glpk/GNU mathprog?
Thanks!
Abhishek
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