```json
{
  "sym_variables": [
    ("x0", "reconnaissance troops"),
    ("x1", "logistics companies"),
    ("x2", "medical platoons")
  ],
  "objective_function": "6*x0**2 + 5*x0*x1 + 9*x1**2 + 3*x1*x2 + 6*x2**2 + x0",
  "constraints": [
    "2.32*x0 + 1.72*x2 <= 26",
    "2.32*x0 + 4.68*x1 <= 17",
    "2.32*x0 + 4.68*x1 + 1.72*x2 <= 17",
    "4.38*x1**2 + 2.0*x2**2 <= 35",
    "4.51*x0 + 2.0*x2 <= 29",
    "4.51*x0 + 4.38*x1 + 2.0*x2 <= 29",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

```python
import gurobipy as gp
from gurobipy import GRB

try:
    # Create a new model
    m = gp.Model("resource_allocation")

    # Create variables
    x0 = m.addVar(vtype=GRB.INTEGER, name="reconnaissance_troops")
    x1 = m.addVar(vtype=GRB.INTEGER, name="logistics_companies")
    x2 = m.addVar(vtype=GRB.INTEGER, name="medical_platoons")


    # Set objective function
    m.setObjective(6*x0**2 + 5*x0*x1 + 9*x1**2 + 3*x1*x2 + 6*x2**2 + x0, GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(2.32*x0 + 1.72*x2 <= 26, "c0")
    m.addConstr(2.32*x0 + 4.68*x1 <= 17, "c1")
    m.addConstr(2.32*x0 + 4.68*x1 + 1.72*x2 <= 17, "c2")
    m.addConstr(4.38*x1**2 + 2.0*x2**2 <= 35, "c3")
    m.addConstr(4.51*x0 + 2.0*x2 <= 29, "c4")
    m.addConstr(4.51*x0 + 4.38*x1 + 2.0*x2 <= 29, "c5")


    # Optimize model
    m.optimize()

    if m.status == GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        print('x0: %g' % x0.x)
        print('x1: %g' % x1.x)
        print('x2: %g' % x2.x)
    elif m.status == GRB.INFEASIBLE:
        print('The model is infeasible.')
    else:
        print('Optimization ended with status %d' % m.status)



except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')
```