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/*
* @author Heinrich Schuchardt <xypron.glpk@gmx.de>
*
* Adapted from an example in C written by
* Andrew Makhorin <mao@gnu.org>, October 2009
*
* LINEAR ORDERING PROBLEM
*
* Let G = (V,E) denote the complete digraph, where V is the set of
* nodes and E is the set of arcs. A tournament T in E consists of a
* subset of arcs containing for every pair of nodes i and j either arc
* (i->j) or arc (j->i), but not both. T is an acyclic tournament if it
* contains no directed cycles. Obviously, an acyclic tournament induces
* an ordering <i1, i2, ..., in> of the nodes (and vice versa), where
* n = |V|. Node i1 is the one with no entering arcs, i2 has exactly one
* entering arc, etc., and in is the node with no outgoing arc. Given
* arc weights w[i,j] for every pair i, j in V, the Linear Ordering
* Problem (LOP) consists of finding an acyclic tournament T in E such
* that the sum of arcs in T is maximal, or in other words, of finding
* an ordering of the nodes such that the sum of the weights of the arcs
* compatible with this ordering is maximal.
*
* Given a nxn-matrix C = (c[i,j]) the triangulation problem is to
* determine a symmetric permutation of the rows and columns of C such
* that the sum of subdiagonal entries is as small as possible. Note
* that it does not matter if diagonal entries are taken into account or
* not. Obviously, by setting arc weights w[i,j] = c[i,j] for the
* complete digraph G, the triangulation problem for C can be solved as
* linear ordering problem for G. Conversely, a linear ordering problem
* for G can be transformed to a triangulation problem for an nxn-matrix
* C by setting c[i,j] = w[i,j] and the diagonal entries c[i,i] = 0 (or
* to arbitrary values).
*
* The LOP can be formulated as binary integer programming problem.
* We use binary variables x[i,j] for (i,j) in A, stating whether arc
* (i->j) is present in the tournament or not. Taking into account that
* a tournament is acyclic iff it contains no dicycles of length 3, it
* is easy to see that the LOP can be formulated as follows:
*
* Maximize
*
* sum w[i,j] x[i,j] (1)
* (i,j) in A
*
* Subject to
*
* x[i,j] + x[j,i] = 1, for all i,j in V, i < j, (2)
*
* x[i,j] + x[j,k] + x[k,i] <= 2, (3)
*
* for all i,j,k in V, i < j, i < k, j != k,
*
* x[i,j] in {0, 1}, for all i,j in V. (4)
*
* (From <http://www.optsicom.es/lolib/#problem-description>.)
*/
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.util.Scanner;
import org.gnu.glpk.GLPK;
import org.gnu.glpk.GLPKConstants;
import org.gnu.glpk.GlpkCallback;
import org.gnu.glpk.GlpkCallbackListener;
import org.gnu.glpk.GlpkException;
import org.gnu.glpk.SWIGTYPE_p_double;
import org.gnu.glpk.SWIGTYPE_p_int;
import org.gnu.glpk.glp_attr;
import org.gnu.glpk.glp_iocp;
import org.gnu.glpk.glp_prob;
import org.gnu.glpk.glp_tree;
/**
* Solves linear ordering problems.
*/
public class LinOrd implements GlpkCallbackListener {
/**
* maximum number of nodes
*/
public final static int N_MAX = 1000;
/**
* number of nodes in the digraph given
*/
int n;
/**
* w[i,j] is weight of arc (i->j), 1 <= i,j <= n
*/
int w[][];
/**
* x[i][j] is the number of binary variable x[i,j], 1 <= i,j <= n, i != j,
* in the problem object, where x[i,j] = 1 means that node i precedes node
* j, i.e. arc (i->j) is included in the tournament
*/
int x[][];
/**
* problem object
*/
glp_prob prob;
/**
* Reads data from file.
*
* @param fname file name
*/
private void read_data(String fname) {
FileReader fr = null;
Scanner sc;
String comment;
int i, j;
try {
fr = new FileReader(fname);
} catch (FileNotFoundException ex) {
System.out.println(ex.getMessage());
System.exit(1);
}
System.out.println("Reading LOP instance data from '"
+ fname
+ "'...");
sc = new Scanner(fr);
comment = sc.nextLine().trim();
System.out.println(comment);
n = sc.nextInt();
if (n < 1) {
System.out.println("invalid number of nodes");
System.exit(1);
}
if (n > N_MAX) {
System.out.println("too many nodes");
System.exit(1);
}
System.out.println("Digraph has " + n + " nodes");
w = new int[1 + n][];
for (i = 1; i <= n; i++) {
w[i] = new int[1 + n];
for (j = 1; j <= n; j++) {
w[i][j] = sc.nextInt();
}
}
try {
fr.close();
} catch (IOException ex) {
System.out.println(ex.getMessage());
System.exit(1);
}
}
/**
* Creates mixed integer problem.
*/
private void build_mip() {
int i, j, row;
SWIGTYPE_p_int ind = GLPK.new_intArray(1 + 2);
SWIGTYPE_p_double val = GLPK.new_doubleArray(1 + 2);
String name;
prob = GLPK.glp_create_prob();
GLPK.glp_set_obj_dir(prob, GLPKConstants.GLP_MAX);
/* create binary variables */
x = new int[1 + n][];
for (i = 1; i <= n; i++) {
x[i] = new int[1 + n];
for (j = 1; j <= n; j++) {
if (i == j) {
x[i][j] = 0;
} else {
x[i][j] = GLPK.glp_add_cols(prob, 1);
name = "x[" + i + "," + j + "]";
GLPK.glp_set_col_name(prob, x[i][j], name);
GLPK.glp_set_col_kind(prob, x[i][j], GLPKConstants.GLP_BV);
/* objective coefficient */
GLPK.glp_set_obj_coef(prob, x[i][j], w[i][j]);
}
}
}
/* create irreflexivity constraints (2) */
for (i = 1; i <= n; i++) {
for (j = i + 1; j <= n; j++) {
row = GLPK.glp_add_rows(prob, 1);
GLPK.glp_set_row_bnds(prob, row, GLPKConstants.GLP_FX, 1, 1);
GLPK.intArray_setitem(ind, 1, x[i][j]);
GLPK.doubleArray_setitem(val, 1, 1.);
GLPK.intArray_setitem(ind, 2, x[j][i]);
GLPK.doubleArray_setitem(val, 2, 1.);
GLPK.glp_set_mat_row(prob, row, 2, ind, val);
}
}
GLPK.delete_intArray(ind);
GLPK.delete_doubleArray(val);
}
/**
* Identifies inactive constraints.
*
* @param tree branch and bound tree
* @param list indices of inactive constraints
* @return number of inactive constraints
*/
private int inactive(glp_tree tree, SWIGTYPE_p_int list) {
glp_attr attr = new glp_attr();
int p = GLPK.glp_ios_curr_node(tree);
int lev = GLPK.glp_ios_node_level(tree, p);
int i, cnt = 0;
for (i = GLPK.glp_get_num_rows(prob); i >= 1; i--) {
GLPK.glp_ios_row_attr(tree, i, attr);
if (attr.getLevel() < lev) {
break;
}
if (attr.getOrigin() != GLPKConstants.GLP_RF_REG) {
if (GLPK.glp_get_row_stat(prob, i) == GLPKConstants.GLP_BS) {
cnt++;
if (list != null) {
GLPK.intArray_setitem(list, cnt, i);
}
}
}
}
System.out.println(cnt + " inactive constraints removed");
return cnt;
}
private void remove_inactive(glp_tree tree) {
/* remove inactive transitivity constraints */
int cnt;
SWIGTYPE_p_int clist;
cnt = inactive(tree, null);
if (cnt > 0) {
clist = GLPK.new_intArray(cnt + 1);
inactive(tree, clist);
GLPK.glp_del_rows(prob, cnt, clist);
}
}
/**
* Generates violated transitivity constraints and adds them to the current
* subproblem. As suggested by Juenger et al., only only arc-disjoint
* violated constraints are considered.
*
* @return number of generated constraints
*/
private int generate_rows() {
int i, j, k, cnt, row;
int[][] u;
SWIGTYPE_p_int ind = GLPK.new_intArray(1 + 3);
SWIGTYPE_p_double val = GLPK.new_doubleArray(1 + 3);
double r;
/* u[i,j] = 1, if arc (i->j) is covered by some constraint */
u = new int[1 + n][];
for (i = 1; i <= n; i++) {
u[i] = new int[1 + n];
for (j = 1; j <= n; j++) {
u[i][j] = 0;
}
}
cnt = 0;
for (i = 1; i <= n; i++) {
for (j = 1; j <= n; j++) {
for (k = 1; k <= n; k++) {
if (i == j) {
} else if (i == k) {
} else if (j == k) {
} else if (u[i][j] != 0 || u[j][i] != 0) {
} else if (u[i][k] != 0 || u[k][i] != 0) {
} else if (u[j][k] != 0 || u[k][j] != 0) {
} else {
/* check if x[i,j] + x[j,k] + x[k,i] <= 2 */
r = GLPK.glp_get_col_prim(prob, x[i][j])
+ GLPK.glp_get_col_prim(prob, x[j][k])
+ GLPK.glp_get_col_prim(prob, x[k][i]);
/* should note that it is not necessary to add to the
current subproblem every violated constraint (3), for
which r > 2; if r < 3, we can stop adding violated
constraints, because for integer feasible solution
the value of r is integer, so r < 3 is equivalent to
r <= 2; on the other hand, adding violated
constraints leads to tightening the feasible region
of LP relaxation and, thus, may reduce the size of
the search tree */
if (r > 2.15) {
/* generate violated transitivity constraint */
row = GLPK.glp_add_rows(prob, 1);
GLPK.glp_set_row_bnds(prob, row,
GLPKConstants.GLP_UP, 0, 2);
GLPK.intArray_setitem(ind, 1, x[i][j]);
GLPK.doubleArray_setitem(val, 1, 1);
GLPK.intArray_setitem(ind, 2, x[j][k]);
GLPK.doubleArray_setitem(val, 2, 1);
GLPK.intArray_setitem(ind, 3, x[k][i]);
GLPK.doubleArray_setitem(val, 3, 1);
GLPK.glp_set_mat_row(prob, row, 3, ind, val);
u[i][j] = u[j][i] = 1;
u[i][k] = u[k][i] = 1;
u[j][k] = u[k][j] = 1;
cnt++;
}
}
}
}
}
GLPK.delete_intArray(ind);
GLPK.delete_doubleArray(val);
System.out.println(cnt + " violated constraints were generated");
return cnt;
}
/**
* Solves a linear ordering problem.
*
* @param inFile input file
* @param outFile output file
*/
private void solve(String inFile, String outFile) {
glp_iocp iocp;
GlpkCallback.addListener(this);
read_data(inFile);
build_mip();
GLPK.glp_adv_basis(prob, 0);
GLPK.glp_simplex(prob, null);
iocp = new glp_iocp();
GLPK.glp_init_iocp(iocp);
GLPK.glp_intopt(prob, iocp);
GLPK.glp_print_mip(prob, outFile);
GlpkCallback.removeListener(this);
GLPK.glp_delete_prob(prob);
}
/**
* Main routine.
*
* @param args command line parameters (input file, output file)
*/
public static void main(String[] args) {
LinOrd l = new LinOrd();
if (args.length != 2) {
System.out.println("Usage: "
+ LinOrd.class.getName()
+ " infile outfile\n\n"
+ "e.g. "
+ LinOrd.class.getName()
+ " tiw56r72.mat solution.txt");
return;
}
try {
l.solve(args[0], args[1]);
} catch (GlpkException ex) {
System.out.println("Program terminated due to an error");
}
}
/**
* Method call by the GLPK MIP solver in the branch-and-cut algorithm.
*
* @param tree search tree
*/
public void callback(glp_tree tree) {
if (GLPK.glp_ios_reason(tree) == GLPKConstants.GLP_IROWGEN) {
remove_inactive(tree);
generate_rows();
}
}
}
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