void CreateStorageBindingConstraint(IloModel model, BoolVar3DMatrix L, BoolVarMatrix M, BoolVarMatrix X, BoolVar3DMatrix R, BoolVarMatrix Y, IloRangeArray c){ IloEnv env = model.getEnv(); //The nested for-loops generate L[p][i][t] //that is required to linearize equation 16 for(int p = 0; p < L.getSize(); p++){ for(int i = 0; i < n; i++){ for(int t = 0; t < T_MAX; t++){ L[p][i].add(IloBoolVar(env)); c.add(L[p][i][t] - M[p][i] - X[i][t] >= -1); c.add(L[p][i][t] - M[p][i] - X[i][t] <= 0); c.add(L[p][i][t] + M[p][i] - X[i][t] <= 1); c.add(L[p][i][t] - M[p][i] + X[i][t] <= 1); } } } //Contructing the array R[p][e][t] for(int p = 0; p < R.getSize(); p++){ for(int e = 0; e < E; e++){ for(int t = 0; t < T_MAX; t++){ R[p][e].add(IloBoolVar(env)); } } } //Encoding the constraint eqn-15 for(int t = 0; t < T_MAX; t++){ IloExprArray sum(env); for(int e = 0; e < E; e++){ sum.add(IloExpr(env)); for(int p = 0; p < n_m; p++){ sum[e] += R[p][e][t]; } c.add(sum[e] - Y[e][t] == 0); } } //Encoding the constraint eqn-21 for(int t = 0; t < T_MAX; t++){ IloExprArray sum1(env); IloExprArray sum2(env); for(int p = 0; p < n_m; p++){ sum1.add(IloExpr(env)); sum2.add(IloExpr(env)); for(int e = 0; e < E; e++) sum1[p] += R[p][e][t]; for(int i = 0; i < n; i++) sum2[p] += L[p][i][t]; c.add(sum1[p] - n_r*sum2[p] <= 0); } } return; }
static void populatebyrow (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); x.add(IloNumVar(env, 0.0, 40.0)); x.add(IloNumVar(env)); x.add(IloNumVar(env)); x.add(IloNumVar(env, 2.0, 3.0, ILOINT)); model.add(IloMaximize(env, x[0] + 2 * x[1] + 3 * x[2] + x[3])); c.add( - x[0] + x[1] + x[2] + 10 * x[3] <= 20); c.add( x[0] - 3 * x[1] + x[2] <= 30); c.add( x[1] - 3.5* x[3] == 0); model.add(c); } // END populatebyrow
static void populatebynonzero (IloModel model, IloIntVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); IloObjective obj = IloMaximize(env); int n, a; scanf("%d", &n); scanf("%d", &a); //restrição c.add(IloRange(env, -IloInfinity, a)); //variaveis for(int i=0 ; i<n; i++){ x.add(IloIntVar(env, 0, 1)); } /*x.add(IloIntVar(env, 0.0, 40.0)); x.add(IloIntVar(env)); x.add(IloIntVar(env));*/ /*obj.setLinearCoef(x[0], 1.0); obj.setLinearCoef(x[1], 2.0); obj.setLinearCoef(x[2], 3.0);*/ /*restricoes*/ for(int i=0 ; i<n; i++){ scanf("%d", &a); c[0].setLinearCoef(x[i], a); } //objetivo for(int i=0 ; i<n; i++){ scanf("%d", &a); obj.setLinearCoef(x[i], a); } /*c[0].setLinearCoef(x[1], 1.0); c[0].setLinearCoef(x[2], 1.0); c[1].setLinearCoef(x[0], 1.0); c[1].setLinearCoef(x[1], -3.0); c[1].setLinearCoef(x[2], 1.0);*/ c[0].setName("c1"); for(int i=0; i<n; i++){ char tmp[10]; printf("x%d", i+1); x[i].setName(tmp); } model.add(obj); model.add(c); } // END populatebynonzero
void generateProblem(const ILPModel& m, IloModel& model, IloNumVarArray& x, IloRangeArray& con) { IloEnv env = model.getEnv(); IloObjective obj = (m.obj == MINIMIZE ? IloMinimize(env) : IloMaximize(env)); for (unsigned long v = 0; v < m.numberOfVariables(); ++v) { switch (m.x[v].type) { case FLT: x.add(IloNumVar(env, m.x[v].lowerBound, m.x[v].upperBound, IloNumVar::Float)); break; case BIN: x.add(IloNumVar(env, m.x[v].lowerBound, m.x[v].upperBound, IloNumVar::Bool)); break; default: x.add(IloNumVar(env, m.x[v].lowerBound, m.x[v].upperBound, IloNumVar::Int)); } obj.setLinearCoef(x[v], m.c[v]); x[v].setName(m.varDesc[v].c_str()); } for (unsigned long c = 0; c < m.numberOfConstraints(); ++c) { switch (m.ops[c]) { case LESS_EQUAL: con.add(IloRange(env, -IloInfinity, m.b[c])); break; case EQUAL: con.add(IloRange(env, m.b[c], m.b[c])); break; case GREATER_EQUAL: con.add(IloRange(env, m.b[c], IloInfinity)); } for (const pair<uint32_t, double>& p : m.A[c]) con[c].setLinearCoef(x[p.first], p.second); con[c].setName(m.conDesc[c].c_str()); } model.add(obj); model.add(con); }
void CreateMixingBindingConstraint(IloModel model, BoolVarMatrix M, BoolVarMatrix Y, BoolVarMatrix X, IloNumVarArray s, IloRangeArray c){ IloEnv env = model.getEnv(); //sum[i] holds summation from //eqn-13 for operation i IloExprArray sum1(env); //Creating array M[p][i] //i is for ith operation for(int p = 0; p < M.getSize(); p++){ for(int i = 0; i < n; i++) M[p].add(IloBoolVar(env)); } //Ensuring operation remains bound to the same module for(int i = 0; i < n; i++){ sum1.add(IloExpr(env)); for(int p = 0; p < n_m; p++){ sum1[i] += M[p][i]; } c.add(sum1[i] == 1); } //Two operations running simulateneously //can not be bound to the same module for(int p = 0; p < n_m; p++){ for(int t = 0; t < T_MAX; t++){ for(int i = 0; i < n; i++){ for(int j = i+1; j < n; j++){ c.add(X[i][t] + X[j][t] + M[p][i] + M[p][j] <= 3); } } } } return; }
void CreateSchedulingConstraint(IloModel model, BoolVarMatrix X, BoolVarMatrix Y, IloNumVarArray s, IloRangeArray c){ IloEnv env = model.getEnv(); //sum[i] holds the summation //from eqn-8 for operation i IloExprArray sum(env); //The for-loop encodes all //the execution constraints for(int i = 0; i < X.getSize(); i++){ sum.add(IloExpr(env)); for(int t = 0; t < T_MAX; t++){ X[i].add(IloBoolVar(env)); sum[i] += X[i][t]; c.add( t - s[i+1] - T_MAX*(X[i][t]-1) >= 0); c.add(-t + s[i+1] - T_MAX*(X[i][t]-1) + T >= 1); } c.add(sum[i] == T); } //Resources Constraints IloExprArray summation1(env); IloExprArray summation2(env); for(int t = 0; t < T_MAX; t++){ summation1.add(IloExpr(env)); summation2.add(IloExpr(env)); for(int i = 0; i < X.getSize(); i++){ summation1[t] += X[i][t]; } for(int e = 0; e < Y.getSize(); e++){ summation2[t] += Y[e][t]; } c.add(n_r*summation1[t] + summation2[t] <= n_m*n_r); } return; }
static void populatebyrow (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); x.add(IloNumVar(env, -1.0, 1.0)); x.add(IloNumVar(env, 0.0, 1.0)); model.add(IloMinimize(env, 0.5 * (-3*x[0]*x[0] - 3*x[1]*x[1] + - 1*x[0]*x[1] ) )); c.add( - x[0] + x[1] >= 0); c.add( x[0] + x[1] >= 0); model.add(c); } // END populatebyrow
static void populatebyrow (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); x.add(IloNumVar(env, 0.0, 40.0)); x.add(IloNumVar(env, 0.0, IloInfinity, ILOINT)); x.add(IloNumVar(env, 0.0, IloInfinity, ILOINT)); x.add(IloNumVar(env, 2.0, 3.0, ILOINT)); model.add(IloMaximize(env, x[0] + 2 * x[1] + 3 * x[2] + x[3])); c.add( - x[0] + x[1] + x[2] + 10 * x[3] <= 20); c.add( x[0] - 3 * x[1] + x[2] <= 30); c.add( x[1] - 3.5* x[3] == 0); model.add(c); IloNumVarArray sosvar(env, 2); IloNumArray sosval(env, 2); sosvar[0] = x[2]; sosvar[1] = x[3]; sosval[0] = 25.0; sosval[1] = 18.0; model.add(IloSOS1(model.getEnv(), sosvar, sosval)); } // END populatebyrow
static void populatebycolumn (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); IloObjective obj = IloMaximize(env); c.add(IloRange(env, -IloInfinity, 20.0)); c.add(IloRange(env, -IloInfinity, 30.0)); x.add(IloNumVar(obj(1.0) + c[0](-1.0) + c[1]( 1.0), 0.0, 40.0)); x.add(obj(2.0) + c[0]( 1.0) + c[1](-3.0)); x.add(obj(3.0) + c[0]( 1.0) + c[1]( 1.0)); model.add(obj); model.add(c); } // END populatebycolumn
static void populatebyrow (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); x.add(IloNumVar(env, 0.0, 40.0)); x.add(IloNumVar(env)); x.add(IloNumVar(env)); model.add(IloMaximize(env, x[0] + 2 * x[1] + 3 * x[2] - 0.5 * (33*x[0]*x[0] + 22*x[1]*x[1] + 11*x[2]*x[2] - 12*x[0]*x[1] - 23*x[1]*x[2] ) )); c.add( - x[0] + x[1] + x[2] <= 20); c.add( x[0] - 3 * x[1] + x[2] <= 30); model.add(c); } // END populatebyrow
ILOSTLBEGIN void makeCuts(IloRangeArray cuts, const IloNumVarArray& vars) { IloNumVar x11, x12, x13, x14, x15; IloNumVar x21, x22, x23, x24, x25; IloNumVar x31, x32, x33, x34, x35; IloNumVar x41, x42, x43, x44, x45; IloNumVar x51, x52, x53, x54, x55; IloNumVar w11, w12, w13, w14, w15; IloNumVar w21, w22, w23, w24, w25; IloNumVar w31, w32, w33, w34, w35; IloNumVar w41, w42, w43, w44, w45; IloNumVar w51, w52, w53, w54, w55; IloInt num = vars.getSize(); for (IloInt i = 0; i < num; i++) { if ( strcmp(vars[i].getName(), "X11") == 0 ) x11 = vars[i]; else if ( strcmp(vars[i].getName(), "X12") == 0 ) x12 = vars[i]; else if ( strcmp(vars[i].getName(), "X13") == 0 ) x13 = vars[i]; else if ( strcmp(vars[i].getName(), "X14") == 0 ) x14 = vars[i]; else if ( strcmp(vars[i].getName(), "X15") == 0 ) x15 = vars[i]; else if ( strcmp(vars[i].getName(), "X21") == 0 ) x21 = vars[i]; else if ( strcmp(vars[i].getName(), "X22") == 0 ) x22 = vars[i]; else if ( strcmp(vars[i].getName(), "X23") == 0 ) x23 = vars[i]; else if ( strcmp(vars[i].getName(), "X24") == 0 ) x24 = vars[i]; else if ( strcmp(vars[i].getName(), "X25") == 0 ) x25 = vars[i]; else if ( strcmp(vars[i].getName(), "X31") == 0 ) x31 = vars[i]; else if ( strcmp(vars[i].getName(), "X32") == 0 ) x32 = vars[i]; else if ( strcmp(vars[i].getName(), "X33") == 0 ) x33 = vars[i]; else if ( strcmp(vars[i].getName(), "X34") == 0 ) x34 = vars[i]; else if ( strcmp(vars[i].getName(), "X35") == 0 ) x35 = vars[i]; else if ( strcmp(vars[i].getName(), "X41") == 0 ) x41 = vars[i]; else if ( strcmp(vars[i].getName(), "X42") == 0 ) x42 = vars[i]; else if ( strcmp(vars[i].getName(), "X43") == 0 ) x43 = vars[i]; else if ( strcmp(vars[i].getName(), "X44") == 0 ) x44 = vars[i]; else if ( strcmp(vars[i].getName(), "X45") == 0 ) x45 = vars[i]; else if ( strcmp(vars[i].getName(), "X51") == 0 ) x51 = vars[i]; else if ( strcmp(vars[i].getName(), "X52") == 0 ) x52 = vars[i]; else if ( strcmp(vars[i].getName(), "X53") == 0 ) x53 = vars[i]; else if ( strcmp(vars[i].getName(), "X54") == 0 ) x54 = vars[i]; else if ( strcmp(vars[i].getName(), "X55") == 0 ) x55 = vars[i]; else if ( strcmp(vars[i].getName(), "W11") == 0 ) w11 = vars[i]; else if ( strcmp(vars[i].getName(), "W12") == 0 ) w12 = vars[i]; else if ( strcmp(vars[i].getName(), "W13") == 0 ) w13 = vars[i]; else if ( strcmp(vars[i].getName(), "W14") == 0 ) w14 = vars[i]; else if ( strcmp(vars[i].getName(), "W15") == 0 ) w15 = vars[i]; else if ( strcmp(vars[i].getName(), "W21") == 0 ) w21 = vars[i]; else if ( strcmp(vars[i].getName(), "W22") == 0 ) w22 = vars[i]; else if ( strcmp(vars[i].getName(), "W23") == 0 ) w23 = vars[i]; else if ( strcmp(vars[i].getName(), "W24") == 0 ) w24 = vars[i]; else if ( strcmp(vars[i].getName(), "W25") == 0 ) w25 = vars[i]; else if ( strcmp(vars[i].getName(), "W31") == 0 ) w31 = vars[i]; else if ( strcmp(vars[i].getName(), "W32") == 0 ) w32 = vars[i]; else if ( strcmp(vars[i].getName(), "W33") == 0 ) w33 = vars[i]; else if ( strcmp(vars[i].getName(), "W34") == 0 ) w34 = vars[i]; else if ( strcmp(vars[i].getName(), "W35") == 0 ) w35 = vars[i]; else if ( strcmp(vars[i].getName(), "W41") == 0 ) w41 = vars[i]; else if ( strcmp(vars[i].getName(), "W42") == 0 ) w42 = vars[i]; else if ( strcmp(vars[i].getName(), "W43") == 0 ) w43 = vars[i]; else if ( strcmp(vars[i].getName(), "W44") == 0 ) w44 = vars[i]; else if ( strcmp(vars[i].getName(), "W45") == 0 ) w45 = vars[i]; else if ( strcmp(vars[i].getName(), "W51") == 0 ) w51 = vars[i]; else if ( strcmp(vars[i].getName(), "W52") == 0 ) w52 = vars[i]; else if ( strcmp(vars[i].getName(), "W53") == 0 ) w53 = vars[i]; else if ( strcmp(vars[i].getName(), "W54") == 0 ) w54 = vars[i]; else if ( strcmp(vars[i].getName(), "W55") == 0 ) w55 = vars[i]; } cuts.add(x21 - x22 <= 0); cuts[0].setName("cut0"); cuts.add(x22 - x23 <= 0); cuts.add(x23 - x24 <= 0); cuts.add(2.08*x11 + 2.98*x21 + 3.47*x31 + 2.24*x41 + 2.08*x51 + 0.25*w11 + 0.25*w21 + 0.25*w31 + 0.25*w41 + 0.25*w51 <= 20.25); cuts.add(2.08*x12 + 2.98*x22 + 3.47*x32 + 2.24*x42 + 2.08*x52 + 0.25*w12 + 0.25*w22 + 0.25*w32 + 0.25*w42 + 0.25*w52 <= 20.25); cuts.add(2.08*x13 + 2.98*x23 + 3.4722*x33 + 2.24*x43 + 2.08*x53 + 0.25*w13 + 0.25*w23 + 0.25*w33 + 0.25*w43 + 0.25*w53 <= 20.25); cuts.add(2.08*x14 + 2.98*x24 + 3.47*x34 + 2.24*x44 + 2.08*x54 + 0.25*w14 + 0.25*w24 + 0.25*w34 + 0.25*w44 + 0.25*w54 <= 20.25); cuts.add(2.08*x15 + 2.98*x25 + 3.47*x35 + 2.24*x45 + 2.08*x55 + 0.25*w15 + 0.25*w25 + 0.25*w35 + 0.25*w45 + 0.25*w55 <= 16.25); }
// This function creates the following model: // Minimize // obj: x1 + x2 + x3 + x4 + x5 + x6 // Subject To // c1: x1 + x2 + x5 = 8 // c2: x3 + x5 + x6 = 10 // q1: [ -x1^2 + x2^2 + x3^2 ] <= 0 // q2: [ -x4^2 + x5^2 ] <= 0 // Bounds // x2 Free // x3 Free // x5 Free // End // which is a second order cone program in standard form. // The function returns objective, variables and constraints in the // values obj, vars and rngs. // The function also sets up cone so that for a column j we have // cone[j] >= 0 Column j is in a cone constraint and is the // cone's head variable. // cone[j] == NOT_CONE_HEAD Column j is in a cone constraint but is // not the cone's head variable.. // cone[j] == NOT_IN_CONE Column j is not contained in any cone constraint. static void createmodel (IloModel& model, IloObjective &obj, IloNumVarArray &vars, IloRangeArray &rngs, IloIntArray& cone) { // The indices we assign as user objects to the modeling objects. // We define them as static data so that we don't have to worry about // dynamic memory allocation/leakage. static int indices[] = { 0, 1, 2, 3, 4, 5, 6 }; IloEnv env = model.getEnv(); // Create variables. IloNumVar x1(env, 0, IloInfinity, "x1"); IloNumVar x2(env, -IloInfinity, IloInfinity, "x2"); IloNumVar x3(env, -IloInfinity, IloInfinity, "x3"); IloNumVar x4(env, 0, IloInfinity, "x4"); IloNumVar x5(env, -IloInfinity, IloInfinity, "x5"); IloNumVar x6(env, 0, IloInfinity, "x6"); // Create objective function and immediately store it in return value. obj = IloMinimize(env, x1 + x2 + x3 + x4 + x5 + x6); // Create constraints. IloRange c1(env, 8, x1 + x2 + x5, 8, "c1"); IloRange c2(env, 10, x3 + x5 + x6, 10, "c2"); IloRange q1(env, -IloInfinity, -x1*x1 + x2*x2 + x3*x3, 0, "q1"); cone.add(2); // x1, cone head of constraint at index 2 cone.add(NOT_CONE_HEAD); // x2 cone.add(NOT_CONE_HEAD); // x3 IloRange q2(env, -IloInfinity, -x4*x4 + x5*x5, 0, "q2"); cone.add(3); // x4, cone head of constraint at index 3 cone.add(NOT_CONE_HEAD); // x5 cone.add(NOT_IN_CONE); // x6 // Setup model. model.add(obj); model.add(obj); model.add(c1); model.add(c2); model.add(q1); model.add(q2); // Setup return values. vars.add(x1); vars.add(x2); vars.add(x3); vars.add(x4); vars.add(x5); vars.add(x6); rngs.add(c1); rngs.add(c2); rngs.add(q1); rngs.add(q2); // We set the user object for each modeling object to its index in the // respective array. This makes the code in checkkkt a little simpler. for (IloInt i = 0; i < vars.getSize(); ++i) vars[i].setObject(&indices[i]); for (IloInt i = 0; i < rngs.getSize(); ++i) rngs[i].setObject(&indices[i]); }
Example(IloEnv env) : nblocks(0), model(env), vars(env), ranges(env) { // Model data. // fixed[] is the fixed cost for opening a facility, // cost[i,j] is the cost for serving customer i from facility j. static double const fixed[] = { 2.0, 3.0, 3.0 }; static double const cost[] = { 2.0, 3.0, 4.0, 5.0, 7.0, 4.0, 3.0, 1.0, 2.0, 6.0, 5.0, 4.0, 2.0, 1.0, 3.0 }; #define NFACTORY ((CPXDIM)(sizeof(fixed) / sizeof(fixed[0]))) #define NCUSTOMER ((CPXDIM)((sizeof(cost) / sizeof(cost[0])) / NFACTORY)) nblocks = NCUSTOMER; IloExpr obj(env); // Create integer y variables. IloNumVarArray y(env); for (IloInt f = 0; f < NFACTORY; ++f) { std::stringstream s; s << "y" << f; IloIntVar v(env, 0, 1, s.str().c_str()); obj += fixed[f] * v; objMap[v] = fixed[f]; y.add(v); blockMap.insert(BlockMap::value_type(v, -1)); intersectMap.insert(IntersectMap::value_type(v, RowSet())); } // Create continuous x variables. IloNumVarArray x(env); for (IloInt f = 0; f < NFACTORY; ++f) { for (IloInt c = 0; c < NCUSTOMER; ++c) { std::stringstream s; s << "x" << f << "#" << c; IloNumVar v(env, 0.0, IloInfinity, s.str().c_str()); obj += v * cost[f * NCUSTOMER + c]; objMap[v] = cost[f * NCUSTOMER + c]; x.add(v); blockMap.insert(BlockMap::value_type(v, c)); intersectMap.insert(IntersectMap::value_type(v, RowSet())); } } vars.add(y); vars.add(x); model.add(vars); // Add objective function. model.add(IloMinimize(env, obj, "obj")); objSense = IloObjective::Minimize; obj.end(); // Satisfy each customer's demand. for (IloInt c = 0; c < NCUSTOMER; ++c) { std::stringstream s; s << "c1_" << c; IloRange r(env, 1.0, IloInfinity, s.str().c_str()); IloExpr lhs(env); for (IloInt f = 0; f < NFACTORY; ++f) { lhs += x[f * NCUSTOMER + c]; intersectMap[x[f * NCUSTOMER + c]].insert(r); } r.setExpr(lhs); ranges.add(r); lhs.end(); } // A factory must be open if we service from it. for (IloInt c = 0; c < NCUSTOMER; ++c) { for (IloInt f = 0; f < NFACTORY; ++f) { std::stringstream s; s << "c2_" << c << "#" << f; IloRange r(env, 0.0, IloInfinity, s.str().c_str()); intersectMap[x[f * NCUSTOMER + c]].insert(r); intersectMap[y[f]].insert(r); r.setExpr(-x[f * NCUSTOMER + c] + y[f]); ranges.add(r); } } // Capacity constraint. IloRange r(env, -IloInfinity, NFACTORY - 1, "c3"); IloExpr lhs(env); for (IloInt f = 0; f < NFACTORY; ++f) { lhs += y[f]; intersectMap[y[f]].insert(r); } r.setExpr(lhs); ranges.add(r); lhs.end(); model.add(ranges); #undef NFACTORY #undef NCUSTOMER }
void LpSolver::populatebyrow (CplexConverter& cplexConverter, IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); // CAPITAL LETTERS MEAN I NEED YOUR HELP, here is help // IloExpr cost(env); // Create Variables // cout << "size of var: " << cplexConverter.variables.size() << endl; for (int i = 0; i < cplexConverter.variables.size(); ++i){ IloNumVar iloVar(env, 0.0, cplexConverter.capacities[i], IloNumVar::Int); // cout << iloVar << endl; x.add(iloVar); } //Capacity Constraints for (auto &it : cplexConverter.atomicIdToVarIdDict){ IloExpr t(env); // cout << "adding constraint "; for (int j = 0; j < it.second.size(); j++){ // cout << "x[" << it.second[j] << "] + "; t += x[it.second[j]]; } // cout << endl; c.add(t <= cplexConverter.graph->atomicEdges[it.first]->capacity); // cout << c << endl; t.end(); } // other constraints for (auto nodePair : cplexConverter.graph->nodes){ // For all nodes Node* n = nodePair.second; if(n == cplexConverter.src){ // source constraints // IloExpr inFlow(env); IloExpr outFlow(env); for(auto &atoIn : n->atomicEdge_in){ int aeId = atoIn.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; outFlow += x[vId]; // cost += cplexConverter.graph->atomicEdges[cplexConverter.variables[vId].atomicEdgeId]->interest_rate * x[vId]; } } for (auto &atoOut : n->atomicEdge_out){ int aeId = atoOut.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; // inFlow += x[vId]; c.add(x[vId] == 0); // cost -= cplexConverter.graph->atomicEdges[cplexConverter.variables[vId].atomicEdgeId]->interest_rate * x[vId]; } } c.add(outFlow == cplexConverter.request); // inFlow.end(); outFlow.end(); } else if(n == cplexConverter.dest){ // destination constraints IloExpr inFlow(env); // IloExpr outFlow(env); for(auto &atoIn : n->atomicEdge_in){ int aeId = atoIn.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; // outFlow += x[vId]; c.add(x[vId] == 0); } } for (auto &atoOut : n->atomicEdge_out){ int aeId = atoOut.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; inFlow += x[vId]; } } c.add(inFlow == cplexConverter.request); inFlow.end(); // outFlow.end(); } else { // Monotonicity Constraints for (int i = 0; i < credNetConstants.totalIrs.size(); ++i){ IloExpr tempin(env); IloExpr tempout(env); for (auto &atoIn : n->atomicEdge_in){ int aeId = atoIn.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; if (cplexConverter.variables[vId].interest_rate <= credNetConstants.totalIrs[i]){ tempout += x[vId]; } } } for (auto &atoOut : n->atomicEdge_out){ int aeId = atoOut.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; if (cplexConverter.variables[vId].interest_rate <= credNetConstants.totalIrs[i]){ tempin += x[vId]; } } } c.add(tempout - tempin >= 0); tempout.end(); tempin.end(); } //Flow Constraints IloExpr inFlow(env); IloExpr outFlow(env); for(auto &atoIn : n->atomicEdge_in){ int aeId = atoIn.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; outFlow += x[vId]; } } for (auto &atoOut : n->atomicEdge_out){ int aeId = atoOut.second->atomicEdgeId; for (int j = 0; j < cplexConverter.atomicIdToVarIdDict[aeId].size(); j++){ // var Id int vId = cplexConverter.atomicIdToVarIdDict[aeId][j]; inFlow += x[vId]; } } c.add(inFlow - outFlow == 0); inFlow.end(); outFlow.end(); } } model.add(c); // model.add(IloMinimize(env, cost)); // model.add(IloMaximize(env,cost)); //option to minimize cost // cost.end(); } // END populatebyrow
static void populatebyrow (IloModel model, IloNumVarArray x, IloRangeArray c) { IloEnv env = model.getEnv(); IloNumArray costs(env); IloNumArray time(env); IloNumArray product(env); int costs_array[] = {1,1,1,10,1,12,2,2,5,10}; int time_array[] = {10,1,7,3,2,3,2,3,7,1}; int product_array[] = {0,3,1,2,-2,0,0,0,0,0}; for(int i=0;i<10;i++) costs.add(costs_array[i]); for(int i=0;i<10;i++) time.add(time_array[i]); for(int i=0;i<10;i++) product.add(product_array[i]); x.add(IloBoolVar(env,"x12")); //0 x.add(IloBoolVar(env,"x24")); //1 x.add(IloBoolVar(env,"x46")); //2 x.add(IloBoolVar(env,"x13")); //3 x.add(IloBoolVar(env,"x32")); //4 x.add(IloBoolVar(env,"x35")); //5 x.add(IloBoolVar(env,"x56")); //6 x.add(IloBoolVar(env,"x25")); //7 x.add(IloBoolVar(env,"x34")); //8 x.add(IloBoolVar(env,"x45")); //9 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s2")); //10 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s3")); //11 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s4")); //12 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s5")); //13 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s1")); //14 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"s6")); //15 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q2")); //16 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q3")); //17 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q4")); //18 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q5")); //19 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q1")); //20 x.add(IloNumVar(env,0,IloInfinity,ILOINT,"q6")); //21 model.add(IloMinimize(env, costs[0]*x[0] + costs[1]*x[1] + costs[2]*x[2] + costs[3]*x[3] + costs[4]*x[4] + costs[5]*x[5] + costs[6]*x[6] + costs[7]*x[7] + costs[8]*x[8] + costs[9]*x[9])); c.add(x[0]+ x[3] == 1); // arcs sortant du noeud de depart c.add(x[2]+ x[6] == 1); // arcs entrant au noeud d arrivee c.add(x[1]+ x[7] - x[0] - x[4] == 0); c.add(x[8]+ x[5] + x[4] - x[3] == 0); c.add(x[9]+ x[2] - x[1] - x[8] == 0); c.add(x[6]- x[7] - x[5] - x[9] == 0); c.add(time[0]*x[0] + time[1]*x[1] + time[2]*x[2] + time[3]*x[3] + time[4]*x[4] + time[5]*x[5] + time[6]*x[6] + time[7]*x[7] + time[8]*x[8] + time[9]*x[9] <= 14); //c.add(product[0]*x[0] + product[1]*x[1] + product[2]*x[2] + product[3]*x[3] + product[4]*x[4] + product[5]*x[5] + product[6]*x[6] + product[7]*x[7] + product[8]*x[8] + product[9]*x[9] <= 4); c.add(x[14]+time[0]-1000*(1-x[0]) - x[10]<= 0); c.add(x[20]+product[0]-1000*(1-x[0]) - x[16]<= 0); c.add(x[10]+time[1]-1000*(1-x[1]) - x[12]<= 0); c.add(x[16]+product[1]-1000*(1-x[1]) - x[18]<= 0); c.add(x[18]-product[1]-1000*(1-x[1]) - x[16]<= 0); c.add(x[12]+time[2]-1000*(1-x[2]) - x[15]<= 0); c.add(x[18]+product[2]-1000*(1-x[2]) - x[21]<= 0); c.add(x[21]-product[2]-1000*(1-x[2]) - x[18]<= 0); c.add(x[14]+time[3]-1000*(1-x[3]) - x[11]<= 0); c.add(x[20]+product[3]-1000*(1-x[3]) - x[17]<= 0); c.add(x[17]-product[3]-1000*(1-x[3]) - x[20]<= 0); c.add(x[13]+time[6]-1000*(1-x[6]) - x[15]<= 0); c.add(x[19]+product[6]-1000*(1-x[6]) - x[21]<= 0); c.add(x[10]+time[7]-1000*(1-x[7]) - x[13]<= 0); c.add(x[16]+product[7]-1000*(1-x[7]) - x[19]<= 0); c.add(x[12]+time[9]-1000*(1-x[9]) - x[13]<= 0); c.add(x[18]+product[9]-1000*(1-x[9]) - x[19]<= 0); c.add(x[11]+time[4]-1000*(1-x[4]) - x[10] <=0); c.add(x[17]+product[4]-1000*(1-x[4]) - x[16]<= 0); c.add(x[16]-product[4]-1000*(1-x[4]) - x[17]<= 0); c.add(x[11]+time[8]-1000*(1-x[8]) - x[12]<= 0); c.add(x[17]+product[8]-1000*(1-x[8]) - x[18]<= 0); c.add(x[11]+time[5]-1000*(1-x[5]) - x[13]<= 0); c.add(x[17]+product[5]-1000*(1-x[5]) - x[19]<= 0); c.add(5 <= x[10] <= 7); c.add(2 <= x[11] <= 5); c.add(5 <= x[12] <= 9); c.add(0 <= x[13] <= 20); c.add(0 <= x[14] <= 0); c.add(0 <= x[15] <= 14); /* c.add(2 <= x[17] <= 4); c.add(0 <= x[16] <= 2); c.add(3 <= x[18] <= 4); c.add(0 <= x[19] <= 1000); //c.add(0 <= x[20] <= 0);*/ c.add(3 <= x[21] <= 4); c.add( x[20] == 1); model.add(c); }