/* Set the name of a variable column */
long __declspec(dllexport) WINAPI _set_col_name(lprec *lp, long column, char *new_name)
{
long ret;
if (lp != NULL) {
freebuferror();
ret = set_col_name(lp, column, new_name);
}
else
ret = 0;
return(ret);
}
// TODO there's a seriouxx need for refactoring here !
Solution LpsolveAdaptator::getAdmissibleSolution(LinearProblem * lp) {
lprec *lprec;
int nbCol = lp->getVariables().size();
lprec = make_lp(0, nbCol);
if (lprec == NULL) {
// TODO raise an exception
}
/* set variables name to ease debugging */
for (int i = 0; i < (int)lp->getVariables().size(); ++i) {
Variable * var = (lp->getVariables())[i];
set_col_name(lprec, i+1, var->getNameToChar());
if (var->isBinary()) {
set_binary(lprec, i+1, TRUE);
}
}
/* to build the model faster when adding constraints one at a time */
set_add_rowmode(lprec, TRUE);
for (int i = 0; i < (int)(lp->getConstraints().size()); ++i) {
// FIXME there's a bug here but I can't find it
Constraint c = (Constraint)(lp->getConstraints()[i]);
TermList terms = c.getTerms();
int col[terms.size()];
REAL row[terms.size()];
int j = 0;
for (TermList::const_iterator it = terms.begin(); it != terms.end();
++it, ++j) {
// TODO check if this is fixed
col[j] = ((Term)*it).getVariable().getPosition();
row[j] = ((Term)*it).getCoeff();
}
// WARNING the Consraint uses the same operator values than in lp_lib.h
if (!add_constraintex(lprec, j, row, col, c.getOperator(), c.getBound())) {
// TODO raise an exception
}
}
/* the objective function requires rowmode to be off */
set_add_rowmode(lprec, FALSE);
return getSolution(lprec);
}
int demoImplicit(void)
{
# if defined ERROR
# undef ERROR
# endif
# define ERROR() { fprintf(stderr, "Error\n"); return(1); }
lprec *lp;
int majorversion, minorversion, release, build;
char buf[1024];
if ((lp = make_lp(0,4)) == NULL)
ERROR();
lp_solve_version(&majorversion, &minorversion, &release, &build);
/* let's first demonstrate the logfunc callback feature */
put_logfunc(lp, Mylogfunc, 0);
sprintf(buf, "lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
print_str(lp, buf);
solve(lp); /* just to see that a message is send via the logfunc routine ... */
/* ok, that is enough, no more callback */
put_logfunc(lp, NULL, 0);
/* Now redirect all output to a file */
/* set_outputfile(lp, "result.txt"); */
/* set an abort function. Again optional */
put_abortfunc(lp, Myctrlcfunc, 0);
/* set a message function. Again optional */
put_msgfunc(lp, Mymsgfunc, 0, MSG_PRESOLVE | MSG_LPFEASIBLE | MSG_LPOPTIMAL | MSG_MILPEQUAL | MSG_MILPFEASIBLE | MSG_MILPBETTER);
printf("lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
printf("This demo will show most of the features of lp_solve %d.%d.%d.%d\n", majorversion, minorversion, release, build);
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp=make_lp(0,4);\n");
press_ret();
printf("We can show the current problem with print_lp(lp)\n");
print_lp(lp);
press_ret();
printf("Now we add some constraints\n");
printf("str_add_constraint(lp, \"3 2 2 1\" ,LE,4)\n");
printf("This is the string version of add_constraint. For the normal version\n");
printf("of add_constraint see the help file.\n");
if (!str_add_constraint(lp, "3 2 2 1", LE, 4))
ERROR();
print_lp(lp);
press_ret();
printf("str_add_constraint(lp, \"0 4 3 1\" ,GE,3)\n");
if (!str_add_constraint(lp, "0 4 3 1", GE, 3))
ERROR();
print_lp(lp);
press_ret();
printf("Set the objective function\n");
printf("str_set_obj_fn(lp, \"2 3 -2 3\")\n");
if (!str_set_obj_fn(lp, "2 3 -2 3"))
ERROR();
print_lp(lp);
press_ret();
printf("Now solve the problem with printf(solve(lp));\n");
printf("%d",solve(lp));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_objective(lp) and print_solution(lp)\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp);\n");
print_duals(lp);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp,2,1,0.5)\n");
if (!set_mat(lp,2,1,0.5))
ERROR();
print_lp(lp);
press_ret();
printf("If we want to maximize the objective function use set_maxim(lp);\n");
set_maxim(lp);
print_lp(lp);
press_ret();
printf("after solving this gives us:\n");
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
print_duals(lp);
press_ret();
printf("Change the value of a rhs element with set_rh(lp,1,7.45)\n");
set_rh(lp,1,7.45);
print_lp(lp);
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We change %s to the integer type with\n", get_col_name(lp, 4));
printf("set_int(lp, 4, TRUE)\n");
set_int(lp, 4, TRUE);
print_lp(lp);
printf("We set branch & bound debugging on with set_debug(lp, TRUE)\n");
set_debug(lp, TRUE);
printf("and solve...\n");
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp,2,2); & set_upbo(lp,4,5.3)\n");
set_lowbo(lp,2,2);
set_upbo(lp,4,5.3);
print_lp(lp);
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Now remove a constraint with del_constraint(lp, 1)\n");
del_constraint(lp,1);
print_lp(lp);
printf("Add an equality constraint\n");
if (!str_add_constraint(lp, "1 2 1 4", EQ, 8))
ERROR();
print_lp(lp);
press_ret();
printf("A column can be added with:\n");
printf("str_add_column(lp,\"3 2 2\");\n");
if (!str_add_column(lp,"3 2 2"))
ERROR();
print_lp(lp);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp,3);\n");
del_column(lp,3);
print_lp(lp);
press_ret();
printf("We can use automatic scaling with:\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
print_lp(lp);
press_ret();
printf("The function get_mat(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s get_mat(lp,2,3), get_mat(lp,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n", (double)get_mat(lp,2,3), (double)get_mat(lp,1,1));
printf("Notice that get_mat returns the value of the original unscaled problem\n");
press_ret();
printf("If there are any integer type variables, then only the rows are scaled\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
printf("set_int(lp,3,FALSE);\n");
set_int(lp,3,FALSE);
print_lp(lp);
press_ret();
solve(lp);
printf("print_objective, print_solution gives the solution to the original problem\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Scaling is turned off with unscale(lp);\n");
unscale(lp);
print_lp(lp);
press_ret();
printf("Now turn B&B debugging off and simplex tracing on with\n");
printf("set_debug(lp, FALSE), set_trace(lp, TRUE) and solve(lp)\n");
set_debug(lp, FALSE);
set_trace(lp, TRUE);
press_ret();
solve(lp);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("default_basis(lp). Now solve it again...\n");
press_ret();
default_basis(lp);
solve(lp);
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp,1,\"speed\"); & set_col_name(lp,2,\"money\")\n");
if (!set_row_name(lp,1,"speed"))
ERROR();
if (!set_col_name(lp,2,"money"))
ERROR();
print_lp(lp);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp,1);\n");
del_column(lp,1);
print_lp(lp);
press_ret();
delete_lp(lp);
/*
printf("A lp structure can be created and read from a .lp file\n");
printf("lp = read_LP(\"lp_examples/demo_lag.lp\", TRUE);\n");
printf("The verbose option is used\n");
if ((lp = read_LP("lp_examples/demo_lag.lp", TRUE, "test")) == NULL)
ERROR();
press_ret();
printf("lp is now:\n");
print_lp(lp);
press_ret();
printf("solution:\n");
set_debug(lp, TRUE);
solve(lp);
set_debug(lp, FALSE);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("You can see that branch & bound was used in this problem\n");
printf("Now remove the last constraint and use lagrangian relaxation\n");
printf("del_constraint(lp,6);\n");
printf("str_add_lag_con(lp, \"1 1 1 0 0 0\", LE, 2);\n");
del_constraint(lp,6);
if (!str_add_lag_con(lp, "1 1 1 0 0 0", LE, 2))
ERROR();
print_lp(lp);
*/
/*
printf("Lagrangian relaxation is used in some heuristics. It is now possible\n");
printf("to get a feasible integer solution without usage of branch & bound.\n");
printf("Use lag_solve(lp, 0, 30); 0 is the initial bound, 30 the maximum\n");
printf("number of iterations, the last variable turns the verbose mode on.\n");
press_ret();
set_lag_trace(lp, TRUE);
printf("%d\n",lag_solve(lp, 0, 30));
printf("The returncode of lag_solve is 6 or FEAS_FOUND. this means that a feasible\n");
printf("solution has been found. For a list of other possible return values\n");
printf("see the help file. Print this solution with print_objective, print_solution\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
delete_lp(lp);
*/
press_ret();
return(0);
}
int MtxLP::addCol(string name, double lb, double ub){
int i = add_cols(1);
set_col_name(i, name.data());
setColBnds(name, lb, ub);
return i;
}
int main(void)
{
lprec *lp1,*lp2;
FILE *input_file;
printf("lp_solve 2.0 demo by Jeroen J. Dirks ([email protected])\n\n");
printf("This demo will show most of the features of lp_solve 2.0\n");
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp1=make_lp(0,4);\n");
lp1=make_lp(0,4);
press_ret();
printf("We can show the current problem with print_lp(lp1)\n");
print_lp(lp1);
press_ret();
printf("Now we add some constraints\n");
printf("str_add_constraint(lp1, \"3 2 2 1\" ,LE,4)\n");
printf("This is the string version of add_constraint. For the normal version\n");
printf("of add_constraint see the file lpkit.h\n");
str_add_constraint(lp1, "3 2 2 1", LE, 4);
print_lp(lp1);
press_ret();
printf("str_add_constraint(lp1, \"0 4 3 1\" ,GE,3)\n");
str_add_constraint(lp1, "0 4 3 1", GE, 3);
print_lp(lp1);
press_ret();
printf("Set the objective function\n");
printf("str_set_obj_fn(lp1, \"2 3 -2 3\")\n");
str_set_obj_fn(lp1, "2 3 -2 3");
print_lp(lp1);
press_ret();
printf("Now solve the problem with printf(solve(lp1));\n");
printf("%d",solve(lp1));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_solution(lp1)\n");
print_solution(lp1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp1);\n");
print_duals(lp1);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp1,2,1,0.5)\n");
set_mat(lp1,2,1,0.5);
print_lp(lp1);
press_ret();
printf("It we want to maximise the objective function use set_maxim(lp1);\n");
set_maxim(lp1);
print_lp(lp1);
press_ret();
printf("after solving this gives us:\n");
solve(lp1);
print_solution(lp1);
print_duals(lp1);
press_ret();
printf("Change the value of a rhs element with set_rh(lp1,1,7.45)\n");
set_rh(lp1,1,7.45);
print_lp(lp1);
solve(lp1);
print_solution(lp1);
press_ret();
printf("We change Var[4] to the integer type with\n");
printf("set_int(lp1, 4, TRUE)\n");
set_int(lp1, 4, TRUE);
print_lp(lp1);
printf("We set branch & bound debugging on with lp1->debug=TRUE\n");
lp1->debug=TRUE;
printf("and solve...\n");
press_ret();
solve(lp1);
print_solution(lp1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp1,2,2); & set_upbo(lp1,4,5.3)\n");
set_lowbo(lp1,2,2);
set_upbo(lp1,4,5.3);
print_lp(lp1);
press_ret();
solve(lp1);
print_solution(lp1);
press_ret();
printf("Now remove a constraint with del_constraint(lp1, 1)\n");
del_constraint(lp1,1);
print_lp(lp1);
printf("Add an equality constraint\n");
str_add_constraint(lp1, "1 2 1 4", EQ, 8);
print_lp(lp1);
press_ret();
printf("A column can be added with:\n");
printf("str_add_column(lp1,\"3 2 2\");\n");
str_add_column(lp1,"3 2 2");
print_lp(lp1);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp1,3);\n");
del_column(lp1,3);
print_lp(lp1);
press_ret();
printf("We can use automatic scaling with:\n");
printf("auto_scale(lp1);\n");
auto_scale(lp1);
print_lp(lp1);
press_ret();
printf("The function mat_elm(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s mat_elm(lp1,2,3), mat_elm(lp1,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n",mat_elm(lp1,2,3), mat_elm(lp1,1,1));
printf("Notice that mat_elm returns the value of the original unscaled problem\n");
press_ret();
printf("It there are any integer type variables, then only the rows are scaled\n");
printf("set_int(lp1,3,FALSE);\n");
printf("auto_scale(lp1);\n");
set_int(lp1,3,FALSE);
auto_scale(lp1);
print_lp(lp1);
press_ret();
solve(lp1);
printf("print_solution gives the solution to the original problem\n");
print_solution(lp1);
press_ret();
printf("Scaling is turned off with unscale(lp1);\n");
unscale(lp1);
print_lp(lp1);
press_ret();
printf("Now turn B&B debugging of and simplex tracing on with\n");
printf("lp1->debug=FALSE, lp1->trace=TRUE and solve(lp1)\n");
lp1->debug=FALSE;
lp1->trace=TRUE;
press_ret();
solve(lp1);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("reset_basis(lp1). Now solve it again...\n");
press_ret();
reset_basis(lp1);
solve(lp1);
press_ret();
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp1,1,\"speed\"); & set_col_name(lp1,2,\"money\")\n");
set_row_name(lp1,1,"speed");
set_col_name(lp1,2,"money");
print_lp(lp1);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp1,1);\n");
del_column(lp1,1);
print_lp(lp1);
press_ret();
printf("A lp structure can be created and read from a .lp file\n");
printf("input_file=fopen(\"lp_examples/demo_lag.lp\",\"r\");\n");
printf("lp2 = read_lp_file(input_file, TRUE);\n");
printf("The verbose option is used\n");
input_file = fopen("lp_examples/demo_lag.lp", "r");
if (input_file == NULL)
{
printf("Can't find demo_lag.lp, stopping\n");
exit(EXIT_FAILURE);
}
lp2 = read_lp_file(input_file, TRUE, "test");
press_ret();
printf("lp2 is now:\n");
print_lp(lp2);
press_ret();
printf("solution:\n");
lp2->debug=TRUE;
solve(lp2);
lp2->debug=FALSE;
print_solution(lp2);
press_ret();
printf("You can see that branch & bound was used in this problem\n");
printf("Now remove the last constraint and use lagrangian relaxation\n");
printf("del_constraint(lp2,6);\n");
printf("str_add_lag_con(lp2, \"1 1 1 0 0 0\", LE, 2);\n");
del_constraint(lp2,6);
str_add_lag_con(lp2, "1 1 1 0 0 0", LE, 2);
print_lp(lp2);
printf("Lagrangian relaxation is used in some heuristics. It is now possible\n");
printf("to get a feasible integer soltution without usage of branch & bound.\n");
printf("Use lag_solve(lp2, 0, 40, TRUE); 0 is the initial bound, 30 the maximum\n");
printf("number of iterations, the last variable turns the verbose mode on.\n");
press_ret();
printf("%d\n",lag_solve(lp2, 0, 30, TRUE));
printf("The returncode of lag_solve is 6 or FEAS_FOUND. this means that a feasible\n");
printf("solution has been found. For a list of other possible return values\n");
printf("see \"lpkit.h\". Print this solution with print_solution\n");
print_solution(lp2);
press_ret();
return(0);
}
int StateConstraints::fireVectorSize(const PetriNet& net,
const MarkVal* m0,
const VarVal*) const{
assert(nPlaces == net.numberOfPlaces());
assert(nVars == net.numberOfVariables());
// Create linary problem
lprec* lp;
lp = make_lp(0, net.numberOfTransitions()); // One variable for each entry in the firing vector
assert(lp);
if(!lp) return false;
// Set verbosity
set_verbose(lp, IMPORTANT);
// Set transition names (not strictly needed)
for(size_t i = 0; i < net.numberOfTransitions(); i++)
set_col_name(lp, i+1, const_cast<char*>(net.transitionNames()[i].c_str()));
// Start adding rows
set_add_rowmode(lp, TRUE);
REAL row[net.numberOfTransitions() + 1];
for(size_t p = 0; p < nPlaces; p++){
// Set row zero
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
for(size_t t = 0; t < net.numberOfTransitions(); t++){
int d = net.outArc(t, p) - net.inArc(p, t);
row[1+t] = d;
}
if(pcs[p].min == pcs[p].max &&
pcs[p].max != CONSTRAINT_INFTY){
double target = pcs[p].min - m0[p];
add_constraint(lp, row, EQ, target);
}else{
// There's always a min, even zero is interesting
double target = pcs[p].min - m0[p];
add_constraint(lp, row, GE, target);
if(pcs[p].max != CONSTRAINT_INFTY){
double target = pcs[p].max - m0[p];
add_constraint(lp, row, LE, target);
}
}
}
// Finished adding rows
set_add_rowmode(lp, FALSE);
// Create objective
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
for(size_t t = 0; t < net.numberOfTransitions(); t++)
row[1+t] = 1; // The sum the components in the firing vector
// Set objective
set_obj_fn(lp, row);
// Minimize the objective
set_minim(lp);
// Set variables as integer variables
for(size_t i = 0; i < net.numberOfTransitions(); i++)
set_int(lp, 1+i, TRUE);
// Attempt to solve the problem
int result = solve(lp);
// Limit on traps to test
size_t traplimit = nPlaces * OVER_APPROX_TRAP_FACTOR;
// Try to add a minimal trap constraint
while((result == OPTIMAL) && traplimit-- < 0){
memset(row, 0, sizeof(REAL) * net.numberOfTransitions() + 1);
// Get the firing vector
get_variables(lp, row);
// Compute the resulting marking
MarkVal rMark[net.numberOfPlaces()];
for(size_t p = 0; p < nPlaces; p++){
rMark[p] = m0[p];
for(size_t t = 0; t < net.numberOfTransitions(); t++)
rMark[p] += (net.outArc(t, p) - net.inArc(p, t)) * (int)row[t];
}
// Find an M-trap
BitField trap(minimalTrap(net, m0, rMark));
//Break if there's no trap
if(trap.none()) break;
// Compute the new equation
for(size_t t = 0; t < net.numberOfTransitions(); t++){
row[1+t] = 0;
for(size_t p = 0; p < nPlaces; p++)
if(trap.test(p))
row[1+t] += net.outArc(t, p) - net.inArc(p, t);
}
// Add a new row with target as greater than equal to 1
set_add_rowmode(lp, TRUE);
add_constraint(lp, row, GE, 1);
set_add_rowmode(lp, FALSE);
// Attempt to solve the again
result = solve(lp);
}
int retval = 0;
if(result != INFEASIBLE){
get_variables(lp, row);
for(size_t t = 0; t < net.numberOfTransitions(); t++)
retval += (int)row[t];
}
// Delete the linear problem
delete_lp(lp);
lp = NULL;
// Return true, if it was infeasible
return retval;
}
int main ( int argv, char * argc[] )
{
# if defined ERROR
# undef ERROR
# endif
# define ERROR() { fprintf(stderr, "Error\n"); exit(1); }
lprec *lp;
int majorversion, minorversion, release, build;
#if defined FORTIFY
Fortify_EnterScope();
#endif
lp_solve_version(&majorversion, &minorversion, &release, &build);
printf("lp_solve %d.%d.%d.%d demo\n\n", majorversion, minorversion, release, build);
printf("This demo will show most of the features of lp_solve %d.%d.%d.%d\n", majorversion, minorversion, release, build);
press_ret();
printf("\nWe start by creating a new problem with 4 variables and 0 constraints\n");
printf("We use: lp=make_lp(0,4);\n");
if ((lp = make_lp(0,4)) == NULL)
ERROR();
press_ret();
printf("We can show the current problem with print_lp(lp)\n");
print_lp(lp);
press_ret();
printf("Now we add some constraints\n");
printf("add_constraint(lp, {0, 3, 2, 2, 1}, LE, 4)\n");
{
double row[] = {0, 3, 2, 2, 1};
if (!add_constraint(lp, row, LE, 4))
ERROR();
}
print_lp(lp);
press_ret();
printf("add_constraintex is now used to add a row. Only the npn-zero values must be specfied with this call.\n");
printf("add_constraintex(lp, 3, {4, 3, 1}, {2, 3, 4}, GE, 3)\n");
{
int colno[] = {2, 3, 4};
double row[] = {4, 3, 1};
if (!add_constraintex(lp, sizeof(colno) / sizeof(*colno), row, colno, GE, 3))
ERROR();
}
print_lp(lp);
press_ret();
printf("Set the objective function\n");
printf("set_obj_fn(lp, {0, 2, 3, -2, 3})\n");
{
double row[] = {0, 2, 3, -2, 3};
if (!set_obj_fn(lp, row))
ERROR();
}
print_lp(lp);
press_ret();
printf("Now solve the problem with printf(solve(lp));\n");
printf("%d",solve(lp));
press_ret();
printf("The value is 0, this means we found an optimal solution\n");
printf("We can display this solution with print_objective(lp) and print_solution(lp)\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("The dual variables of the solution are printed with\n");
printf("print_duals(lp);\n");
print_duals(lp);
press_ret();
printf("We can change a single element in the matrix with\n");
printf("set_mat(lp,2,1,0.5)\n");
if (!set_mat(lp,2,1,0.5))
ERROR();
print_lp(lp);
press_ret();
printf("If we want to maximize the objective function use set_maxim(lp);\n");
set_maxim(lp);
print_lp(lp);
press_ret();
printf("after solving this gives us:\n");
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
print_duals(lp);
press_ret();
printf("Change the value of a rhs element with set_rh(lp,1,7.45)\n");
set_rh(lp,1,7.45);
print_lp(lp);
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We change %s to the integer type with\n", get_col_name(lp, 4));
printf("set_int(lp, 4, TRUE)\n");
set_int(lp, 4, TRUE);
print_lp(lp);
printf("We set branch & bound debugging on with set_debug(lp, TRUE)\n");
set_debug(lp, TRUE);
printf("and solve...\n");
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("We can set bounds on the variables with\n");
printf("set_lowbo(lp,2,2); & set_upbo(lp,4,5.3)\n");
set_lowbo(lp,2,2);
set_upbo(lp,4,5.3);
print_lp(lp);
press_ret();
solve(lp);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Now remove a constraint with del_constraint(lp, 1)\n");
del_constraint(lp,1);
print_lp(lp);
printf("Add an equality constraint\n");
{
double row[] = {0, 1, 2, 1, 4};
if (!add_constraint(lp, row, EQ, 8))
ERROR();
}
print_lp(lp);
press_ret();
printf("A column can be added with:\n");
printf("add_column(lp,{3, 2, 2});\n");
{
double col[] = {3, 2, 2};
if (!add_column(lp, col))
ERROR();
}
print_lp(lp);
press_ret();
printf("A column can be removed with:\n");
printf("del_column(lp,3);\n");
del_column(lp,3);
print_lp(lp);
press_ret();
printf("We can use automatic scaling with:\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
print_lp(lp);
press_ret();
printf("The function get_mat(lprec *lp, int row, int column) returns a single\n");
printf("matrix element\n");
printf("%s get_mat(lp,2,3), get_mat(lp,1,1); gives\n","printf(\"%f %f\\n\",");
printf("%f %f\n", (double)get_mat(lp,2,3), (double)get_mat(lp,1,1));
printf("Notice that get_mat returns the value of the original unscaled problem\n");
press_ret();
printf("If there are any integer type variables, then only the rows are scaled\n");
printf("set_scaling(lp, SCALE_MEAN);\n");
set_scaling(lp, SCALE_MEAN);
printf("set_int(lp,3,FALSE);\n");
set_int(lp,3,FALSE);
print_lp(lp);
press_ret();
solve(lp);
printf("print_objective, print_solution gives the solution to the original problem\n");
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
printf("Scaling is turned off with unscale(lp);\n");
unscale(lp);
print_lp(lp);
press_ret();
printf("Now turn B&B debugging off and simplex tracing on with\n");
printf("set_debug(lp, FALSE), set_trace(lp, TRUE) and solve(lp)\n");
set_debug(lp, FALSE);
set_trace(lp, TRUE);
press_ret();
solve(lp);
printf("Where possible, lp_solve will start at the last found basis\n");
printf("We can reset the problem to the initial basis with\n");
printf("default_basis(lp). Now solve it again...\n");
press_ret();
default_basis(lp);
solve(lp);
printf("It is possible to give variables and constraints names\n");
printf("set_row_name(lp,1,\"speed\"); & set_col_name(lp,2,\"money\")\n");
if (!set_row_name(lp,1,"speed"))
ERROR();
if (!set_col_name(lp,2,"money"))
ERROR();
print_lp(lp);
printf("As you can see, all column and rows are assigned default names\n");
printf("If a column or constraint is deleted, the names shift place also:\n");
press_ret();
printf("del_column(lp,1);\n");
del_column(lp,1);
print_lp(lp);
press_ret();
write_lp(lp, "lp.lp");
delete_lp(lp);
printf("An lp structure can be created and read from a .lp file\n");
printf("lp = read_lp(\"lp.lp\", TRUE);\n");
printf("The verbose option is used\n");
if ((lp = read_LP("lp.lp", TRUE, "test")) == NULL)
ERROR();
press_ret();
printf("lp is now:\n");
print_lp(lp);
press_ret();
printf("solution:\n");
set_debug(lp, TRUE);
solve(lp);
set_debug(lp, FALSE);
print_objective(lp);
print_solution(lp, 1);
print_constraints(lp, 1);
press_ret();
delete_lp(lp);
#if defined FORTIFY
Fortify_LeaveScope();
#endif
return 0;
}
//Execute function
int LPSolveClass::Execute()
{
/*
std::cout << "---------------------------------\n";
std::cout << "objective function\n";
for (unsigned int i = 0; i < coefficients.size(); i++)
std::cout << coefficients[i] << "\t";
std::cout << "\nConstant Value = " << obj_const << std::endl;
std::cout << "---------------------------------\n";
std::cout << "Equality Constraints\n";
for (unsigned int i = 0; i < A_equ.size(); i++){
//std::cout << "Row index = " << i << "\t\t";
for (unsigned int j = 0; j < A_equ[i].size(); j++)
std::cout << A_equ[i][j] << "\t";
std::cout << "\n";
}
std::cout << "b\n";
for (unsigned int i = 0; i < b_equ.size(); i++)
std::cout << b_equ[i] << "\t";
std::cout << "\n";
std::cout << "---------------------------------\n";
std::cout << "InEquality Constraints\n";
for (unsigned int i = 0; i < A_inequ.size(); i++){
//std::cout << "Row index = " << i << "\t\t";
for (unsigned int j = 0; j < A_inequ[i].size(); j++)
std::cout << A_inequ[i][j] << "\t";
std::cout << "\n";
}
std::cout << "b\n";
for (unsigned int i = 0; i < b_inequ.size(); i++)
std::cout << b_inequ[i] << "\t";
std::cout << "\n";
*/
lprec *lp;
int Ncol = coefficients.size(), *colno = NULL, j, ret = 0;
REAL *row = NULL;
/* We will build the model row by row
So we start with creating a model with 0 rows and n columns */
lp = make_lp(0, Ncol);
if (lp == NULL)
ret = 1;/* couldn't construct a new model... */
if (ret == 0){
//let us name our variables
std::string s = "x";
for (int i = 0; i < Ncol; i++){
std::stringstream out;
out << i;
s = s + out.str();
char *cpy = new char[s.size()+1] ;
strcpy(cpy, s.c_str());
set_col_name(lp, i+1, cpy);
}
/* create space large enough for one row */
colno = (int *) malloc(Ncol * sizeof(*colno));
row = (REAL *) malloc(Ncol * sizeof(*row));
if ((colno == NULL) || (row == NULL))
ret = 2;
}
set_add_rowmode(lp, TRUE);
//add the equation constraints
if (ret == 0){
/* makes building the model faster if it is done rows by row */
if (A_equ.size() > 0){
for (unsigned int i = 0; i < A_equ.size(); i++){//loop over the rows of equality constraints
for (unsigned int j = 0; j < A_equ[i].size(); j++){//loop over the columns of equality constraints
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = A_equ[i][j];
}
/* add the row to lpsolve */
if(!add_constraintex(lp, A_equ[i].size(), row, colno, EQ, b_equ[i]))
ret = 2;
}
}
}
//add the inequality constraints
if (ret == 0){
/* makes building the model faster if it is done rows by row */
if (A_inequ.size() > 0){
for (unsigned int i = 0; i < A_inequ.size(); i++){//loop over the rows of inequality constraints
for (unsigned int j = 0; j < A_inequ[i].size(); j++){//loop over the columns of inequality constraints
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = A_inequ[i][j];
}
/* add the row to lpsolve */
if(!add_constraintex(lp, A_inequ[i].size(), row, colno, LE, b_inequ[i]))
ret = 3;
}
}
}
//add the const constraint
if (ret == 0){
if (b_const.size()>0){
for (unsigned int i = 0; i < b_const.size(); i++){
if (b_const[i] > 0){
for (unsigned int j = 0; j < b_const.size(); j++){
if (i == j){
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = 1.0;
}
else{
colno[j] = j+1;//add the j-th column to lpsolve
row[j] = 0.0;
}
}
if(!add_constraintex(lp, b_const.size(), row, colno, EQ, b_const[i]))
ret = 4;
}
}
}
}
//set the variables to be integer
if (ret == 0){
for (int i = 0; i < Ncol; i++)
set_int(lp, i+1, TRUE);
}
/* rowmode should be turned off again when done building the model */
set_add_rowmode(lp, FALSE);
//add the objective function
if (ret == 0){
//set the objective function
for (unsigned int i = 0; i < coefficients.size(); i++){
colno[i] = i+1;
row[i] = coefficients[i];
}
//set the objective in lpsolve
if(!set_obj_fnex(lp, coefficients.size(), row, colno))
ret = 4;
}
//set the objective to minimize
if (ret == 0){
set_minim(lp);
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP(lp, stdout);
/* I only want to see important messages on screen while solving */
set_verbose(lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
//get some results
if (ret == 0){
/* a solution is calculated, now lets get some results */
/* objective value */
std::cout << "Objective value: " << get_objective(lp) << std::endl;
/* variable values */
get_variables(lp, row);
/* variable values */
variables.resize(Ncol);
for(j = 0; j < Ncol; j++)
variables[j] = row[j];
/* we are done now */
}
else{
std::cout << "The optimal value can't be solved for linear programming, please check the constraints!!\n";
exit(1);
}
std::cout << "print the result\t # of line segments is \n";
for (int i = 0; i < Ncol; i++)
std::cout << "index = " << i << "\t# = " << variables[i] << std::endl;
/* free allocated memory */
if(row != NULL)
free(row);
if(colno != NULL)
free(colno);
/* clean up such that all used memory by lpsolve is freed */
if (lp != NULL)
delete_lp(lp);
return ret;
}
void CLPLpsolve::setFunction(CLPFunction* function)
{
m_status = 0;
m_lpFunction = function;
const int nVars = function->getNumCoefficients();
// Creates an empty problem with getNumCoefficients variables
m_env = make_lp(0, nVars);
if(m_env == NULL)
{
m_status = 1;
}
//if(!set_add_rowmode(m_env, FALSE))
//{
// m_status = 1;
//}
//Allowing memory for rows
//int * colno = new int[nVars];
REAL * row= new REAL[nVars + 1];
//set variables names
for (int i = 0; i < nVars; ++i)
{
int lpIndex = i + 1;
row[lpIndex] = function->getCoefficients().at(i);
//colno[i] = lpIndex;
//Determines the type
switch(function->getIntegers().at(i)) {
case 'C' :
m_status = set_unbounded(m_env, lpIndex);
break;
case 'B' :
m_status = set_binary(m_env, lpIndex, TRUE);
break;
case 'I' :
m_status = set_int(m_env, lpIndex, TRUE);
break;
case 'S' :
m_status = set_semicont(m_env, lpIndex, TRUE);
break;
default:
assert(false);
break;
}
//Sets upper bound and lower bound
set_upbo(m_env, lpIndex, function->getUpperBounds().at(i));
set_lowbo(m_env, lpIndex, function->getLowerBounds().at(i));
set_col_name(m_env, lpIndex, const_cast<char*>(function->getVarNames().at(i).c_str()));
}
//set_obj_fnex(m_env, nVars, row, colno);
set_obj_fn(m_env, row);
// Set the type of the problem (Min or Max)
switch (function->getType()) {
case lpMinFunction:
set_minim(m_env);
break;
case lpMaxFunction:
set_maxim(m_env);
break;
}
if(!set_add_rowmode(m_env, TRUE))
{
m_status = 1;
}
delete [] row;
}
double solve_constraints(int this_task)
{
lprec *lp;
int numVar = 0, *var = NULL, ret = 0, i, j, k, var_count;
double *coeff = NULL, lhs,rhs, obj;
char col_name[10];
/* Creating a model */
for(i = 1;i < this_task; i++)
numVar+=i;
lp = make_lp(0, numVar);
if(lp == NULL)
ret = 1; /* Couldn't construct a new model */
if(ret == 0) {
var_count = 1;
for(i = 1 ; i < this_task; i++){
for(j = i+1 ; j <= this_task; j++)
{
sprintf(col_name, "%dNNP%d_%d", this_task, i, j);
set_col_name(lp, var_count, col_name);
var_count++;
}
}
/* create space large enough for one row(i.e. equation) */
var = (int *) malloc(numVar * sizeof(*var));
coeff = (double *) malloc(numVar * sizeof(*coeff));
if((var == NULL) || (coeff == NULL))
ret = 2;
}
/* add the equations to lpsolve */
if(ret == 0) {
set_add_rowmode(lp, TRUE);
/* --------------------adding EQN-D-------------------- */
for(j = 2;j <= this_task;j++){
var_count = 0;
for(i = 1; i < j; i++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
lhs= 0;
for(i = 1; i < j; i++)
lhs+= nnp_min[i][j];
lhs*= floor(R[this_task]/task[j].p);
rhs = 0;
for(i = 1; i < j; i++)
rhs += nnp_max[i][j];
rhs *= ceil(R[this_task]/task[j].p);
if(!add_constraintex(lp, var_count, coeff, var, GE, lhs))
ret = 3;
if(!add_constraintex(lp, var_count, coeff, var, LE, rhs))
ret = 3;
}
}
if(ret == 0) {
/* --------------------adding EQN-E-------------------- */
for(k = 2;k <= this_task;k++)
{
var_count = 0;
for(j = 2; j <= k; j++){
for(i = 1; i < j; i++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
}
rhs = 0;
for(i = 1; i < k; i++)
rhs += ceil(R[this_task]/task[i].p);
if(!add_constraintex(lp, var_count, coeff, var, LE,rhs))
ret = 3;
}
}
if(ret == 0) {
/* ------------------adding EQN-G & H------------------ */
for(j = 2; j <= this_task ; j++){
for(i = 1; i < j; i++){
lhs= floor(R[this_task]/task[j].p) * nnp_min[i][j];
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[0] = get_nameindex(lp, col_name, FALSE);
coeff[0] = 1;
if(!add_constraintex(lp, 1, coeff, var, GE, lhs))
ret = 3;
rhs = min(ceil(R[this_task]/task[i].p), ceil(R[this_task]/task[j].p) * ceil(R[j]/task[i].p), ceil(R[this_task]/task[j].p) * nnp_max[i][j]);
if(!add_constraintex(lp, 1, coeff, var, LE,rhs))
ret = 3;
}
}
}
if(ret == 0) {
/* --------------------adding EQN-I-------------------- */
for(i = 1; i < this_task; i++){
var_count = 0;
for(j = i+1; j <= this_task; j++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = 1;
var_count++;
}
rhs = ceil(R[this_task]/task[i].p);
if(!add_constraintex(lp, var_count, coeff, var, LE,rhs))
ret = 3;
}
}
set_add_rowmode(lp, FALSE);
if(ret == 0) {
/* -----------------set the objective----------------- */
var_count = 0;
for(i = 1 ; i < this_task; i++){
for(j = i+1 ; j<= this_task; j++){
sprintf(col_name,"%dNNP%d_%d",this_task, i, j);
var[var_count] = get_nameindex(lp, col_name, FALSE);
coeff[var_count] = get_f(this_task, i, j);
var_count++;
}
}
if(!set_obj_fnex(lp, var_count, coeff, var))
ret = 4;
set_maxim(lp);
write_LP(lp, stdout);
set_verbose(lp, IMPORTANT);
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
if(ret == 0) {
obj = get_objective(lp);
/* Displaying calculated values */
/* variable values */
printf("\nVariable values:\n");
get_variables(lp, coeff);
printf("\n");
for(j = 0; j < numVar; j++)
printf("%s: %f\n", get_col_name(lp, j + 1), coeff[j]);
/* objective value */
printf("\nObjective value: %f\n\n", obj);
}
printf("LP ERROR = %d\n\n", ret);
/* free allocated memory */
if(coeff != NULL)
free(coeff);
if(var != NULL)
free(var);
if(lp != NULL)
delete_lp(lp);
return ret == 0 ? obj : 0;
}
int calculate (IN int nCols /* variables in the model */,
IN int nRows,
IN double** rows,
IN double* rights,
IN double* objectives,
OUT int* answer,
IN int verbose)
{
lprec *lp;
int result = 0;
char *str = NULL;
int *colno = NULL;
double *row = NULL;
/* We will build the model row by row
* So we start with creating a model
* with 0 rows and 2 columns
*/
if ( !(lp = make_lp (0, nCols)) )
{
/* couldn't construct a new model... */
result = 1;
goto RESULT;
}
if ( !(str = (char*) malloc ((log10 (nCols) + 10) * sizeof (*str))) )
{
result = 2;
goto RESULT;
}
/* let us name our variables. Not required,
* but can be useful for debugging
*/
for ( int i = 1; i <= nCols; ++i )
{
str[0] = 't';
_itoa (i, str + 1, 10);
set_col_name (lp, i, str);
// set_int (lp, i, TRUE);
}
/* create space large enough for one row */
colno = (int *) malloc (nCols * sizeof (*colno));
row = (double*) malloc (nCols * sizeof (*row));
if ( (colno == NULL) || (row == NULL) )
{
result = 2;
goto RESULT;
}
for ( int j = 0; j < nCols; ++j )
{ colno[j] = j + 1; /* (j + 1) column */ }
/* makes building the model faster if it is done rows by row */
set_add_rowmode (lp, TRUE);
for ( int i = 0; i < nRows; ++i )
{
// /* construct j row */
// for ( int j = 0; j < nCols; ++j )
// { row[j] = ??? ; }
/* (210 * t2 + 156 * t3 == 0.0178) */
/* (230 * t2 + 160 * t3 == 0.0176) */
/* add the row to lp_solve */
if ( !add_constraintex (lp, nCols, rows[i], colno, EQ, rights[i]) )
{
result = 3;
goto RESULT;
}
}
/* rowmode should be turned off again when done building the model */
set_add_rowmode (lp, FALSE);
// /* set the objective function */
// for ( int j = 0; j < nCols; ++j )
// { row[j] = objectives[j]; }
/* (t1 + t2 + t3 + t4) */
/* set the objective in lp_solve */
if ( !set_obj_fnex (lp, nCols, objectives, colno) )
{
result = 4;
goto RESULT;
}
/* set the object direction to maximize */
set_minim (lp);
if ( verbose )
{
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP (lp, stdout);
/* write_lp(lp, "model.lp"); */
}
/* I only want to see important messages on screen while solving */
set_verbose (lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
result = solve (lp);
if ( result == OPTIMAL )
{ result = 0; }
else
{
result = 5;
goto RESULT;
}
/* a solution is calculated,
* now lets get some results
*/
if ( verbose )
{
/* objective value */
printf ("Objective value: %f\n", get_objective (lp));
}
/* variable values */
get_variables (lp, row);
for ( int j = 0; j < nCols; j++ )
{
if ( verbose )
printf ("%s: %f\n", get_col_name (lp, j + 1), row[j]);
answer[j] = row[j];
}
/* we are done now */
RESULT:;
/* free allocated memory */
if ( str != NULL )free (str);
if ( row != NULL ) free (row);
if ( colno != NULL ) free (colno);
if ( lp != NULL )
{
/* clean up such that all used memory by lpsolve is freed */
delete_lp (lp);
}
return result;
}
int demo()
{
lprec *lp;
int Ncol, *colno = NULL, j, ret = 0;
REAL *row = NULL;
/* We will build the model row by row
So we start with creating a model with 0 rows and 2 columns */
Ncol = 2; /* there are two variables in the model */
lp = make_lp(0, Ncol);
if(lp == NULL)
ret = 1; /* couldn't construct a new model... */
if(ret == 0) {
/* let us name our variables. Not required, but can be useful for debugging */
set_col_name(lp, 1, "x");
set_col_name(lp, 2, "y");
/* create space large enough for one row */
colno = (int *) malloc(Ncol * sizeof(*colno));
row = (REAL *) malloc(Ncol * sizeof(*row));
if((colno == NULL) || (row == NULL))
ret = 2;
}
if(ret == 0) {
set_add_rowmode(lp, TRUE); /* makes building the model faster if it is done rows by row */
/* construct first row (120 x + 210 y <= 15000) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 120;
colno[j] = 2; /* second column */
row[j++] = 210;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 15000))
ret = 3;
}
if(ret == 0) {
/* construct second row (110 x + 30 y <= 4000) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 110;
colno[j] = 2; /* second column */
row[j++] = 30;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 4000))
ret = 3;
}
if(ret == 0) {
/* construct third row (x + y <= 75) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 1;
colno[j] = 2; /* second column */
row[j++] = 1;
/* add the row to lpsolve */
if(!add_constraintex(lp, j, row, colno, LE, 75))
ret = 3;
}
if(ret == 0) {
set_add_rowmode(lp, FALSE); /* rowmode should be turned off again when done building the model */
/* set the objective function (143 x + 60 y) */
j = 0;
colno[j] = 1; /* first column */
row[j++] = 143;
colno[j] = 2; /* second column */
row[j++] = 60;
/* set the objective in lpsolve */
if(!set_obj_fnex(lp, j, row, colno))
ret = 4;
}
if(ret == 0) {
/* set the object direction to maximize */
set_maxim(lp);
/* just out of curioucity, now show the model in lp format on screen */
/* this only works if this is a console application. If not, use write_lp and a filename */
write_LP(lp, stdout);
/* write_lp(lp, "model.lp"); */
/* I only want to see important messages on screen while solving */
set_verbose(lp, IMPORTANT);
/* Now let lpsolve calculate a solution */
ret = solve(lp);
if(ret == OPTIMAL)
ret = 0;
else
ret = 5;
}
if(ret == 0) {
/* a solution is calculated, now lets get some results */
/* objective value */
printf("Objective value: %f\n", get_objective(lp));
/* variable values */
get_variables(lp, row);
for(j = 0; j < Ncol; j++)
printf("%s: %f\n", get_col_name(lp, j + 1), row[j]);
/* we are done now */
}
/* free allocated memory */
if(row != NULL)
free(row);
if(colno != NULL)
free(colno);
if(lp != NULL) {
/* clean up such that all used memory by lpsolve is freed */
delete_lp(lp);
}
return(ret);
}