# Revision history [back]

### MixedIntegerProgramming with more tha 2 indexes

Some integer linear programming needs more indexes than two. But this works

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(x[i,t] for t in range(10)) for i in range(5)));
p.add_constraint(sum(sum(x[i,t] for t in range(10)) for i in range(5))<=1);
p.show()


and this doesn't.

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5)))for j in range(5));
p.add_constraint(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5))) for j in range(5));
p.show()


Is there a way out ?

### MixedIntegerProgramming with more tha 2 indexes

Some integer linear programming needs more indexes than two. But this works

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(x[i,t] for t in range(10)) for i in range(5)));
p.add_constraint(sum(sum(x[i,t] for t in range(10)) for i in range(5))<=1);
p.show()


and this doesn't.

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5)))for j in range(5));
p.add_constraint(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5))) for j in range(5));
p.show()


Is there a way out ?

I would ask for uniformity of notations. The code for sum() is not the same in Linear programming and outside. This is missleading.

### MixedIntegerProgramming with more tha 2 indexes

Some integer linear programming needs more indexes than two. But this works

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(x[i,t] for t in range(10)) for i in range(5)));
p.add_constraint(sum(sum(x[i,t] for t in range(10)) for i in range(5))<=1);
p.show()


and this doesn't.

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5)))for j in range(5));
p.add_constraint(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5))) for j in range(5));
p.show()


Is there a way out ?

I would ask for uniformity of notations. The code for sum() is not the same in Linear programming and outside. This is missleading.

### MixedIntegerProgramming with more tha than 2 indexes

Some integer linear programming needs more indexes than two. But this works

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(x[i,t] for t in range(10)) for i in range(5)));
p.add_constraint(sum(sum(x[i,t] for t in range(10)) for i in range(5))<=1);
p.show()


and this doesn't.

p = MixedIntegerLinearProgram(maximization=False, solver="GLPK")
x = p.new_variable(integer=True, nonnegative=True)
p.set_objective(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5)))for j in range(5));
p.add_constraint(sum(sum(sum(x[i,j,t] for t in range(10)) for i in range(5))) for j in range(5));
p.show()


Is there a way out ?

I would ask for uniformity of notations. The code for sum() is not the same in Linear programming and outside. This is missleading.