glpk.h

著名的大规模线性规划求解器源码GLPK.C语言版本,可以修剪.内有详细帮助文档.

      /* pointer to the head endpoint */
      void *data;
      /* pointer to data associated with the arc */
      void *temp;
      /* working pointer */
      glp_arc *t_prev;
      /* pointer to previous arc having the same tail endpoint */
      glp_arc *t_next;
      /* pointer to next arc having the same tail endpoint */
      glp_arc *h_prev;
      /* pointer to previous arc having the same head endpoint */
      glp_arc *h_next;
      /* pointer to next arc having the same head endpoint */
};

glp_graph *glp_create_graph(int v_size, int a_size);
/* create graph */

void glp_set_graph_name(glp_graph *G, const char *name);
/* assign (change) graph name */

int glp_add_vertices(glp_graph *G, int nadd);
/* add new vertices to graph */

glp_arc *glp_add_arc(glp_graph *G, int i, int j);
/* add new arc to graph */

void glp_erase_graph(glp_graph *G, int v_size, int a_size);
/* erase graph content */

void glp_delete_graph(glp_graph *G);
/* delete graph */

void glp_mincost_lp(glp_prob *lp, glp_graph *G, int names, int v_rhs,
      int a_low, int a_cap, int a_cost);
/* convert minimum cost flow problem to LP */

int glp_mincost_okalg(glp_graph *G, int v_rhs, int a_low, int a_cap,
      int a_cost, double *sol, int a_x, int v_pi);
/* find minimum-cost flow with out-of-kilter algorithm */

void glp_maxflow_lp(glp_prob *lp, glp_graph *G, int names, int s,
      int t, int a_cap);
/* convert maximum flow problem to LP */

int glp_maxflow_ffalg(glp_graph *G, int s, int t, int a_cap,
      double *sol, int a_x, int v_cut);
/* find maximal flow with Ford-Fulkerson algorithm */

int glp_read_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap,
      int a_cost, const char *fname);
/* read min-cost flow problem data in DIMACS format */

int glp_write_mincost(glp_graph *G, int v_rhs, int a_low, int a_cap,
      int a_cost, const char *fname);
/* write min-cost flow problem data in DIMACS format */

int glp_read_maxflow(glp_graph *G, int *s, int *t, int a_cap,
      const char *fname);
/* read maximum flow problem data in DIMACS format */

int glp_write_maxflow(glp_graph *G, int s, int t, int a_cap,
      const char *fname);
/* write maximum flow problem data in DIMACS format */

int glp_netgen(glp_graph *G, int v_rhs, int a_cap, int a_cost,
      const int parm[1+15]);
/* Klingman's network problem generator */

int glp_gridgen(glp_graph *G, int v_rhs, int a_cap, int a_cost,
      const int parm[1+14]);
/* grid-like network problem generator */

int glp_rmfgen(glp_graph *G, int *s, int *t, int a_cap,
      const int parm[1+5]);
/* Goldfarb's maximum flow problem generator */

int glp_weak_comp(glp_graph *G, int v_num);
/* find all weakly connected components of graph */

/**********************************************************************/

#define LPX glp_prob

/* problem class: */
#define LPX_LP          100   /* linear programming (LP) */
#define LPX_MIP         101   /* mixed integer programming (MIP) */

/* type of auxiliary/structural variable: */
#define LPX_FR          110   /* free variable */
#define LPX_LO          111   /* variable with lower bound */
#define LPX_UP          112   /* variable with upper bound */
#define LPX_DB          113   /* double-bounded variable */
#define LPX_FX          114   /* fixed variable */

/* optimization direction flag: */
#define LPX_MIN         120   /* minimization */
#define LPX_MAX         121   /* maximization */

/* status of primal basic solution: */
#define LPX_P_UNDEF     132   /* primal solution is undefined */
#define LPX_P_FEAS      133   /* solution is primal feasible */
#define LPX_P_INFEAS    134   /* solution is primal infeasible */
#define LPX_P_NOFEAS    135   /* no primal feasible solution exists */

/* status of dual basic solution: */
#define LPX_D_UNDEF     136   /* dual solution is undefined */
#define LPX_D_FEAS      137   /* solution is dual feasible */
#define LPX_D_INFEAS    138   /* solution is dual infeasible */
#define LPX_D_NOFEAS    139   /* no dual feasible solution exists */

/* status of auxiliary/structural variable: */
#define LPX_BS          140   /* basic variable */
#define LPX_NL          141   /* non-basic variable on lower bound */
#define LPX_NU          142   /* non-basic variable on upper bound */
#define LPX_NF          143   /* non-basic free variable */
#define LPX_NS          144   /* non-basic fixed variable */

/* status of interior-point solution: */
#define LPX_T_UNDEF     150   /* interior solution is undefined */
#define LPX_T_OPT       151   /* interior solution is optimal */

/* kind of structural variable: */
#define LPX_CV          160   /* continuous variable */
#define LPX_IV          161   /* integer variable */

/* status of integer solution: */
#define LPX_I_UNDEF     170   /* integer solution is undefined */
#define LPX_I_OPT       171   /* integer solution is optimal */
#define LPX_I_FEAS      172   /* integer solution is feasible */
#define LPX_I_NOFEAS    173   /* no integer solution exists */

/* status codes reported by the routine lpx_get_status: */
#define LPX_OPT         180   /* optimal */
#define LPX_FEAS        181   /* feasible */
#define LPX_INFEAS      182   /* infeasible */
#define LPX_NOFEAS      183   /* no feasible */
#define LPX_UNBND       184   /* unbounded */
#define LPX_UNDEF       185   /* undefined */

/* exit codes returned by solver routines: */
#define LPX_E_OK        200   /* success */
#define LPX_E_EMPTY     201   /* empty problem */
#define LPX_E_BADB      202   /* invalid initial basis */
#define LPX_E_INFEAS    203   /* infeasible initial solution */
#define LPX_E_FAULT     204   /* unable to start the search */
#define LPX_E_OBJLL     205   /* objective lower limit reached */
#define LPX_E_OBJUL     206   /* objective upper limit reached */
#define LPX_E_ITLIM     207   /* iterations limit exhausted */
#define LPX_E_TMLIM     208   /* time limit exhausted */
#define LPX_E_NOFEAS    209   /* no feasible solution */
#define LPX_E_INSTAB    210   /* numerical instability */
#define LPX_E_SING      211   /* problems with basis matrix */
#define LPX_E_NOCONV    212   /* no convergence (interior) */
#define LPX_E_NOPFS     213   /* no primal feas. sol. (LP presolver) */
#define LPX_E_NODFS     214   /* no dual feas. sol. (LP presolver) */
#define LPX_E_MIPGAP    215   /* relative mip gap tolerance reached */

/* control parameter identifiers: */
#define LPX_K_MSGLEV    300   /* lp->msg_lev */
#define LPX_K_SCALE     301   /* lp->scale */
#define LPX_K_DUAL      302   /* lp->dual */
#define LPX_K_PRICE     303   /* lp->price */
#define LPX_K_RELAX     304   /* lp->relax */
#define LPX_K_TOLBND    305   /* lp->tol_bnd */
#define LPX_K_TOLDJ     306   /* lp->tol_dj */
#define LPX_K_TOLPIV    307   /* lp->tol_piv */
#define LPX_K_ROUND     308   /* lp->round */
#define LPX_K_OBJLL     309   /* lp->obj_ll */
#define LPX_K_OBJUL     310   /* lp->obj_ul */
#define LPX_K_ITLIM     311   /* lp->it_lim */
#define LPX_K_ITCNT     312   /* lp->it_cnt */
#define LPX_K_TMLIM     313   /* lp->tm_lim */
#define LPX_K_OUTFRQ    314   /* lp->out_frq */
#define LPX_K_OUTDLY    315   /* lp->out_dly */
#define LPX_K_BRANCH    316   /* lp->branch */
#define LPX_K_BTRACK    317   /* lp->btrack */
#define LPX_K_TOLINT    318   /* lp->tol_int */
#define LPX_K_TOLOBJ    319   /* lp->tol_obj */
#define LPX_K_MPSINFO   320   /* lp->mps_info */
#define LPX_K_MPSOBJ    321   /* lp->mps_obj */
#define LPX_K_MPSORIG   322   /* lp->mps_orig */
#define LPX_K_MPSWIDE   323   /* lp->mps_wide */
#define LPX_K_MPSFREE   324   /* lp->mps_free */
#define LPX_K_MPSSKIP   325   /* lp->mps_skip */
#define LPX_K_LPTORIG   326   /* lp->lpt_orig */
#define LPX_K_PRESOL    327   /* lp->presol */
#define LPX_K_BINARIZE  328   /* lp->binarize */
#define LPX_K_USECUTS   329   /* lp->use_cuts */
#define LPX_K_BFTYPE    330   /* lp->bfcp->type */
#define LPX_K_MIPGAP    331   /* lp->mip_gap */

#define LPX_C_COVER     0x01  /* mixed cover cuts */
#define LPX_C_CLIQUE    0x02  /* clique cuts */
#define LPX_C_GOMORY    0x04  /* Gomory's mixed integer cuts */
#define LPX_C_MIR       0x08  /* mixed integer rounding cuts */
#define LPX_C_ALL       0xFF  /* all cuts */

typedef struct
{     /* this structure contains results reported by the routines which
         checks Karush-Kuhn-Tucker conditions (for details see comments
         to those routines) */
      /*--------------------------------------------------------------*/
      /* xR - A * xS = 0 (KKT.PE) */
      double pe_ae_max;
      /* largest absolute error */
      int    pe_ae_row;
      /* number of row with largest absolute error */
      double pe_re_max;
      /* largest relative error */
      int    pe_re_row;
      /* number of row with largest relative error */
      int    pe_quality;
      /* quality of primal solution:
         'H' - high
         'M' - medium
         'L' - low
         '?' - primal solution is wrong */
      /*--------------------------------------------------------------*/
      /* l[k] <= x[k] <= u[k] (KKT.PB) */
      double pb_ae_max;
      /* largest absolute error */
      int    pb_ae_ind;
      /* number of variable with largest absolute error */
      double pb_re_max;
      /* largest relative error */
      int    pb_re_ind;
      /* number of variable with largest relative error */
      int    pb_quality;
      /* quality of primal feasibility:
         'H' - high
         'M' - medium
         'L' - low
         '?' - primal solution is infeasible */
      /*--------------------------------------------------------------*/
      /* A' * (dR - cR) + (dS - cS) = 0 (KKT.DE) */
      double de_ae_max;
      /* largest absolute error */
      int    de_ae_col;
      /* number of column with largest absolute error */
      double de_re_max;
      /* largest relative error */
      int    de_re_col;
      /* number of column with largest relative error */
      int    de_quality;
      /* quality of dual solution:
         'H' - high
         'M' - medium
         'L' - low
         '?' - dual solution is wrong */
      /*--------------------------------------------------------------*/
      /* d[k] >= 0 or d[k] <= 0 (KKT.DB) */
      double db_ae_max;
      /* largest absolute error */
      int    db_ae_ind;
      /* number of variable with largest absolute error */
      double db_re_max;
      /* largest relative error */
      int    db_re_ind;
      /* number of variable with largest relative error */
      int    db_quality;
      /* quality of dual feasibility:
         'H' - high
         'M' - medium
         'L' - low
         '?' - dual solution is infeasible */
      /*--------------------------------------------------------------*/
      /* (x[k] - bound of x[k]) * d[k] = 0 (KKT.CS) */
      double cs_ae_max;
      /* largest absolute error */
      int    cs_ae_ind;
      /* number of variable with largest absolute error */
      double cs_re_max;
      /* largest relative error */
      int    cs_re_ind;
      /* number of variable with largest relative error */
      int    cs_quality;
      /* quality of complementary slackness:
         'H' - high
         'M' - medium
         'L' - low
         '?' - primal and dual solutions are not complementary */
} LPXKKT;

#define lpx_create_prob _glp_lpx_create_prob
LPX *lpx_create_prob(void);
/* create problem object */

#define lpx_set_prob_name _glp_lpx_set_prob_name
void lpx_set_prob_name(LPX *lp, const char *name);
/* assign (change) problem name */

#define lpx_set_obj_name _glp_lpx_set_obj_name
void lpx_set_obj_name(LPX *lp, const char *name);
/* assign (change) objective function name */

#define lpx_set_obj_dir _glp_lpx_set_obj_dir
void lpx_set_obj_dir(LPX *lp, int dir);
/* set (change) optimization direction flag */

#define lpx_add_rows _glp_lpx_add_rows
int lpx_add_rows(LPX *lp, int nrs);
/* add new rows to problem object */

#define lpx_add_cols _glp_lpx_add_cols
int lpx_add_cols(LPX *lp, int ncs);
/* add new columns to problem object */

#define lpx_set_row_name _glp_lpx_set_row_name
void lpx_set_row_name(LPX *lp, int i, const char *name);
/* assign (change) row name */

#define lpx_set_col_name _glp_lpx_set_col_name
void lpx_set_col_name(LPX *lp, int j, const char *name);
/* assign (change) column name */

#define lpx_set_row_bnds _glp_lpx_set_row_bnds
void lpx_set_row_bnds(LPX *lp, int i, int type, double lb, double ub);
/* set (change) row bounds */

#define lpx_set_col_bnds _glp_lpx_set_col_bnds
void lpx_set_col_bnds(LPX *lp, int j, int type, double lb, double ub);
/* set (change) column bounds */

#define lpx_set_obj_coef _glp_lpx_set_obj_coef
void lpx_set_obj_coef(glp_prob *lp, int j, double coef);
/* set (change) obj. coefficient or constant term */

#define lpx_set_mat_row _glp_lpx_set_mat_row
void lpx_set_mat_row(LPX *lp, int i, int len, const int ind[],
      const double val[]);
/* set (replace) row of the constraint matrix */

#define lpx_set_mat_col _glp_lpx_set_mat_col
void lpx_set_mat_col(LPX *lp, int j, int len, const int ind[],
      const double val[]);
/* set (replace) column of the constraint matrix */

#define lpx_load_matrix _glp_lpx_load_matrix
void lpx_load_matrix(LPX *lp, int ne, const int ia[], const int ja[],
      const double ar[]);
/* load (replace) the whole constraint matrix */

#define lpx_del_rows _glp_lpx_del_rows
void lpx_del_rows(LPX *lp, int nrs, const int num[]);
/* delete specified rows from problem object */

#define lpx_del_cols _glp_lpx_del_cols
void lpx_del_cols(LPX *lp, int ncs, const int num[]);
/* delete specified columns from problem object */

#define lpx_delete_prob _glp_lpx_delete_prob
void lpx_delete_prob(LPX *lp);
/* delete problem object */

#define lpx_get_prob_name _glp_lpx_get_prob_name
const char *lpx_get_prob_name(LPX *lp);
/* retrieve problem name */

#define lpx_get_obj_name _glp_lpx_get_obj_name
const char *lpx_get_obj_name(LPX *lp);
/* retrieve objective function name */

#define lpx_get_obj_dir _glp_lpx_get_obj_dir
int lpx_get_obj_dir(LPX *lp);
/* retrieve optimization direction flag */

#define lpx_get_num_rows _glp_lpx_get_num_rows
int lpx_get_num_rows(LPX *lp);
/* retrieve number of rows */

#define lpx_get_num_cols _glp_lpx_get_num_cols
int lpx_get_num_cols(LPX *lp);
/* retrieve number of columns */

#define lpx_get_row_name _glp_lpx_get_row_name