/**
* Optimizes the objective while also optimizing the sum of absolute values of fluxes.
*
* @return the GLPK status of the solver
*/
private synchronized int runOptimizeSumAbsoluteValuesFluxes() {
// First run - deal with objective flux.
int ret = -1;
if (objStyle == FBAModel.MIN_OBJECTIVE_MAX_TOTAL
|| objStyle == FBAModel.MIN_OBJECTIVE_MIN_TOTAL) GLPK.glp_set_obj_dir(lp, GLPK.GLP_MIN);
else GLPK.glp_set_obj_dir(lp, GLPK.GLP_MAX);
if (objStyle == FBAModel.MAX_OBJECTIVE_MIN_TOTAL
|| objStyle == FBAModel.MIN_OBJECTIVE_MIN_TOTAL) GLPK.glp_set_obj_dir(lpMSA, GLPK.GLP_MIN);
else GLPK.glp_set_obj_dir(lpMSA, GLPK.GLP_MAX);
// setup done.
int status = -1; // GLPK.glp_simplex(lp, param);
simParam.setPresolve(GLPK.GLP_OFF);
switch (glpkSolverMethod) {
case SIMPLEX_METHOD:
status = GLPK.glp_simplex(lp, simParam);
break;
default:
status = GLPK.glp_interior(lp, intParam);
break;
}
if (status != 0) return status;
// now, fetch the objective solution from lp, and fix it as the
// upper and lower bounds to lpMSA
double sol = GLPK.glp_get_obj_val(lp);
GLPK.glp_set_col_bnds(lpMSA, objReaction, GLPK.GLP_FX, sol, sol);
// ret = GLPK.glp_simplex(lpMSA, param);
switch (glpkSolverMethod) {
case SIMPLEX_METHOD:
ret = GLPK.glp_simplex(lpMSA, simParam);
break;
default:
ret = GLPK.glp_interior(lpMSA, intParam);
break;
}
return ret;
}
/**
* Internally initializes and resets the parameters used by GLPK. If you want to set specific GLPK
* parameters, you'll need to call a specialized function. //TODO make this possible...
*/
public void setParameters() {
simParam = new glp_smcp();
GLPK.glp_init_smcp(simParam);
intParam = new glp_iptcp();
GLPK.glp_init_iptcp(intParam);
GLPK.glp_init_smcp(simParam);
GLPK.glp_init_iptcp(intParam);
// assume lpsolver == 1, and the rest = default, for now.
// remap of control parameters for simplex method
simParam.setMsg_lev(GLPKConstants.GLP_MSG_OFF);
intParam.setMsg_lev(GLPKConstants.GLP_MSG_OFF);
// simplex method: primal/dual
switch (GLPIntParam[2]) {
case 0:
simParam.setMeth(GLPKConstants.GLP_PRIMAL);
break;
case 1:
simParam.setMeth(GLPKConstants.GLP_DUAL);
break;
case 2:
simParam.setMeth(GLPKConstants.GLP_DUALP);
break;
default:
break;
}
// pricing technique
if (GLPIntParam[3] == 0) simParam.setPricing(GLPKConstants.GLP_PT_STD);
else simParam.setPricing(GLPKConstants.GLP_PT_PSE);
// ratio test
if (GLPIntParam[20] == 0) simParam.setR_test(GLPKConstants.GLP_RT_STD);
else simParam.setR_test(GLPKConstants.GLP_RT_HAR);
// tolerances
simParam.setTol_bnd(GLPRealParam[1]); // primal feasible tolerance
simParam.setTol_dj(GLPRealParam[2]); // dual feasible tolerance
simParam.setTol_piv(GLPRealParam[3]); // pivot tolerance
simParam.setObj_ll(GLPRealParam[4]); // lower limit
simParam.setObj_ul(GLPRealParam[5]); // upper limit
// iteration limit
if (GLPIntParam[5] == -1) simParam.setIt_lim(Integer.MAX_VALUE);
else simParam.setIt_lim(GLPIntParam[5]);
// time limit
if (GLPRealParam[6] == -1) simParam.setTm_lim(Integer.MAX_VALUE);
else simParam.setTm_lim((int) GLPRealParam[6]);
simParam.setOut_frq(GLPIntParam[7]); // output frequency
simParam.setOut_dly((int) GLPRealParam[7]); // output delay
// presolver
if (GLPIntParam[16] != 0) simParam.setPresolve(GLPK.GLP_ON);
else simParam.setPresolve(GLPK.GLP_OFF);
}
