/* Set the upperbound of a variable */
long __declspec(dllexport) WINAPI _set_upbo(lprec *lp, long column, double value)
{
long ret;
if (lp != NULL) {
freebuferror();
ret = set_upbo(lp, column, value);
}
else
ret = 0;
return(ret);
}
int CLPLpsolve::changeBds(int varIndex, const char* lowOrUpper, double bound)
{
if (stricmp(lowOrUpper, "L") == 0)
m_status = set_lowbo(m_env, varIndex + 1, bound);
else if (stricmp(lowOrUpper, "U") == 0)
m_status = set_upbo(m_env, varIndex + 1, bound);
else
assert(false);
return getStatus();
}
/*
Solve the LP subproblem by calling lp_solve API
*/
int LLW_solve_lp(double **gradient, const struct TrainingCache *cache, const struct Model *model)
{
long i,k,l,ind_pattern,y_i;
const long Q = model->Q;
const double Qd = (double)Q;
const long chunk_size = cache->chunk_size;
const double *C = model->C;
const int nRows = Q-1;
const int nCols = chunk_size * Q;
double *obj = (double*)malloc(sizeof(double) * (1+nCols));
double *row = (double*)malloc(sizeof(double) * (1+nCols));
double *rhs = (double*)malloc(sizeof(double) * Q);
long **lp_sol_table = matrix_l(nCols, 2);
long **lp_sol_table_inv = matrix_l(chunk_size, Q);
double *sol = (double*)malloc(sizeof(double) * (1+nRows+nCols));
double epsel;
// Make LP
lprec *lp = make_lp(0, nCols);
set_add_rowmode(lp, TRUE);
// Make objective function
int col = 1;
for(i=1; i<=chunk_size; i++)
{
ind_pattern = cache->table_chunk[i];
for(k=1; k<=Q; k++)
{
obj[col] = gradient[ind_pattern][k];
lp_sol_table[col][1] = i; // keep a table of correspondance between
lp_sol_table[col][2] = k; // LPSOLVE vector of variables and lp_sol matrix
lp_sol_table_inv[i][k] = col++; // lp_sol[i][k] = the 'lp_solve_table_inv[i][k]'-th variable for LPSOLVE
}
}
set_obj_fn(lp, obj);
/* // Make RHS of constraints
// -- complete computation --
for(k=1; k<Q; k++)
{
rhs[k] = 0.0;
for(i=1; i<=nb_data; i++)
if(cache->in_chunk[i] == 0)
{
for(l=1; l<=Q; l++)
rhs[k] += model->alpha[i][l];
rhs[k] -= Qd * model->alpha[i][k];
}
}
*/
// Make RHS of constraints
// -- updates to cache->rhs are made in compute_new_alpha()
// to keep track of rhs
// we only need to remove the contribution of the examples in the chunk
for(k=1; k<Q; k++)
{
rhs[k] = cache->lp_rhs[k];
for(i=1; i<=chunk_size; i++)
{
ind_pattern = cache->table_chunk[i];
for(l=1; l<=Q; l++)
rhs[k] -= model->alpha[ind_pattern][l];
rhs[k] += Qd * model->alpha[ind_pattern][k];
}
}
// Make constraints
for(k=1; k<Q; k++)
{
for(col = 1;col <=nCols; col++)
row[col] = 0.0;
for(i=1; i<=chunk_size; i++)
{
ind_pattern = cache->table_chunk[i];
y_i = model->y[ind_pattern];
for(l=1; l<=Q; l++)
if(l != y_i)
{
row[lp_sol_table_inv[i][l]] = -1.0;
if(l == k)
row[lp_sol_table_inv[i][l]] += Qd;
}
}
add_constraint(lp, row, EQ, rhs[k]);
}
// Upper bound constraints: alpha <= Cy_i
for(col=1;col<=nCols;col++)
set_upbo(lp, col, C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]);
/*
for(i=1; i<=chunk_size; i++) {
for(k=1; k<=Q; k++)
if(k != model->y[cache->table_chunk[i]]) {
col = (int)lp_sol_table_inv[i][k];
set_upbo(lp, col, C);
}
}
*/
// End of LP making
set_add_rowmode(lp, FALSE);
//print_lp(lp);
// Solve LP
int jump = false;
set_outputfile(lp,"");
if(solve(lp)) {
printf("Problem with the LP... \n");
jump = true;
}
else {
// Recover solution in the matrix lp_sol
get_primal_solution(lp, sol); // sol: template for lp_solve solution format
// sol=[obj, constraints, variables]
epsel = get_epsel(lp); // tolerance in lp_solve
// Put solution into lp_sol
for(col=1; col<= nCols; col++) {
// Check feasibility of the col-th variable
if((sol[nRows+col] < -epsel) || (sol[nRows+col] > C[model->y[cache->table_chunk[lp_sol_table[col][1]]]] + epsel)) {
jump = true;
break;
}
// Round off tolerance
if(fabs(sol[nRows+col]) < epsel)
sol[nRows+col] = 0.0;
else if(fabs(sol[nRows+col] - C[model->y[cache->table_chunk[lp_sol_table[col][1]]]]) < epsel)
sol[nRows+col] = C[model->y[cache->table_chunk[lp_sol_table[col][1]]]];
// Set the value in lp_sol matrix
cache->lp_sol[lp_sol_table[col][1]][lp_sol_table[col][2]] = sol[nRows+col];
}
}
delete_lp(lp);
free(obj);
free(row);
free(rhs);
free(lp_sol_table[1]);free(lp_sol_table);
free(lp_sol_table_inv[1]);free(lp_sol_table_inv);
free(sol);
return jump;
}
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 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);
}
main(int argc, char **argv)
#endif
{
char *stub;
ASL *asl;
FILE *nl;
lprec *lp;
ograd *og;
int ct, i, intmin, *is, j, j0, j1, k, nalt, rc;
short *basis, *lower;
real *LU, *c, lb, objadj, *rshift, *shift, t, ub, *x, *x0, *x1;
char buf[256];
typedef struct { char *msg; int code; } Sol_info;
static Sol_info solinfo[] = {
{ "optimal", 0 },
{ "integer programming failure", 502 },
{ "infeasible", 200 },
{ "unbounded", 300 },
{ "failure", 501 },
{ "bug", 500 }
};
sprintf(lp_solve_version+9, "%.*s", (int)sizeof(lp_solve_version)-10,
PATCHLEVEL);
sprintf(lp_solve_vversion, "%s, driver(20001002)", lp_solve_version);
asl = ASL_alloc(ASL_read_f);
stub = getstub(&argv, &Oinfo);
nl = jac0dim(stub, (fint)strlen(stub));
suf_declare(suftab, sizeof(suftab)/sizeof(SufDecl));
/* set A_vals to get the constraints column-wise */
A_vals = (real *)M1alloc(nzc*sizeof(real));
f_read(nl,0);
lp = make_lp(n_con, 0);
Oinfo.uinfo = (char *)lp;
if (getopts(argv, &Oinfo))
return 1;
i = n_var + n_con + 1;
x = (real*)M1alloc(i*sizeof(real)); /* scratch vector */
memset(x, 0, i*sizeof(real));
x0 = x++;
c = x + n_con;
/* supply objective */
objadj = 0;
if (--nobj >= 0 && nobj < n_obj) {
for(og = Ograd[nobj]; og; og = og->next)
c[og->varno] = og->coef;
if (objtype[nobj])
set_maxim(lp);
objadj = objconst(nobj);
}
/* supply columns and variable bounds */
LU = LUv;
intmin = n_var - (nbv + niv);
j1 = nalt = 0;
rshift = shift = 0;
for(i = 1; i <= n_var; i++, LU += 2) {
lb = LU[0];
ub = LU[1];
j0 = j1;
j1 = A_colstarts[i];
*x0 = *c++; /* cost coefficient */
if (lb <= negInfinity && ub < Infinity) {
/* negate this variable */
nalt++;
lb = -ub;
ub = -LU[0];
for(j = j0; j < j1; j++)
x[A_rownos[j]] = -A_vals[j];
*x0 = -*x0;
add_column(lp, x0);
if (lb)
goto shift_check;
}
else {
for(j = j0; j < j1; j++)
x[A_rownos[j]] = A_vals[j];
add_column(lp, x0);
if (lb <= negInfinity) {
nalt++;
if (i > intmin)
set_int(lp, lp->columns, TRUE);
/* split free variable */
*x0 = -*x0;
for(j = j0; j < j1; j++)
x[A_rownos[j]] *= -1.;
add_column(lp,x0);
}
else if (lb) {
shift_check:
if (lb > 0)
set_lowbo(lp, lp->columns, lb);
else {
if (!rshift) {
rshift = (real*)M1zapalloc(
(n_var+n_con)*sizeof(real));
shift = rshift + n_con - 1;
}
shift[i] = lb;
for(j = j0; j < j1; j++) {
k = A_rownos[j];
rshift[k] += lb*x[k];
}
if (ub < Infinity)
ub -= lb;
objadj += lb**x0;
}
}
if (ub < Infinity)
set_upbo(lp, lp->columns, ub);
}
for(j = j0; j < j1; j++)
x[A_rownos[j]] = 0;
if (i > intmin)
set_int(lp, lp->columns, TRUE);
}
if (objadj) {
/* add a fixed variable to adjust the objective value */
*x0 = objadj;
add_column(lp, x0);
set_lowbo(lp, i, 1.);
set_upbo(lp, i, 1.);
}
/* supply constraint rhs */
LU = LUrhs;
for(i = 1; i <= n_con; i++, LU += 2) {
t = LU[0];
if (t == LU[1])
ct = EQ;
else if (t <= negInfinity) {
t = LU[1];
if (t >= Infinity) {
/* This is possible only with effort: */
/* one must turn presolve off and */
/* explicitly specify a constraint */
/* with infinite bounds. */
fprintf(Stderr,
"Sorry, can't handle free rows.\n");
exit(1);
}
ct = LE;
}
else
ct = GE;
set_constr_type(lp, i, ct);
set_rh(lp, i, rshift ? t - *rshift++ : t);
if (ct == GE && LU[1] < Infinity)
lp->orig_upbo[i] = LU[1] - t;
}
if (prlp)
print_lp(lp);
if (scaling)
auto_scale(lp);
/* Unfortunately, there seems to be no way to suggest */
/* a starting basis to lp_solve; thus we must ignore */
/* any incoming .sstatus values. */
rc = solve(lp);
if (rc < 0 || rc > 5)
rc = 5;
solve_result_num = solinfo[rc].code;
i = sprintf(buf, "%s: %s", Oinfo.bsname, solinfo[rc].msg);
if (rc == OPTIMAL)
i += sprintf(buf+i, ", objective %.*g", obj_prec(),
lp->best_solution[0]);
i += sprintf(buf+i,"\n%d simplex iterations", lp->total_iter);
if (lp->max_level > 1 || lp->total_nodes > 1)
sprintf(buf+i, "\n%d branch & bound nodes: depth %d",
lp->total_nodes, lp->max_level);
/* Prepare to report solution: deal with split free variables. */
x1 = lp->best_solution+lp->rows+1;
if (nalt || shift) {
x = x0;
LU = LUv;
for(i = 0; i < n_var; i++, LU += 2) {
if (LU[0] > negInfinity)
x[i] = *x1++;
else if (LU[1] < Infinity)
x[i] = -*x1++;
else {
x[i] = x1[0] - x1[1];
x1 += 2;
}
if (shift)
x[i] += *++shift;
}
}
else
x = x1;
if (solinfo[rc].code < 500 && !(nbv + niv)) {
/* return .sstatus values */
basis = lp->basis;
lower = lp->lower;
is = M1alloc((n_var + n_con)*sizeof(int));
suf_iput("sstatus", ASL_Sufkind_con, is);
for(i = 0; i < n_con; i++) {
j = *++lower;
*is++ = *++basis ? 1 : j ? 3 : 4;
}
suf_iput("sstatus", ASL_Sufkind_var, is);
LU = LUv;
for(i = 0; i < n_var; i++, LU += 2) {
j0 = *++basis;
j1 = *++lower;
if (LU[0] > negInfinity)
j = j0 ? 1 : j1 ? 3 : 4;
else if (LU[1] < Infinity)
j = j0 ? 1 : j1 ? 4 : 3;
else {
++lower;
j = *++basis || j0;
}
*is++ = j;
}
}
write_sol(buf, x, lp->duals+1, &Oinfo);
/* The following calls would only be needed */
/* if execution were to continue... */
delete_lp(lp);
ASL_free(&asl);
return 0;
}
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;
}
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;
}