## Step 1: Define the symbolic representation of the variables
The variables are 'engineer platoons', 'reconnaissance troops', and 'CBRN platoons', which can be represented symbolically as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the natural language description into a symbolic representation
The symbolic representation of the variables is:
- $x_0$ : engineer platoons
- $x_1$ : reconnaissance troops
- $x_2$ : CBRN platoons

## 3: Define the objective function in symbolic notation
The objective function to maximize is $3x_0 + 7x_1 + 6x_2$.

## 4: List the constraints in symbolic notation
The constraints are:
- $4x_0 + 6x_1 + x_2 \geq 40$ (deployment weight of at least 40 metric tons)
- $12x_0 + 14x_2 \geq 30$ (total combined offensive capability rating from engineer platoons and CBRN platoons)
- $12x_0 + 3x_1 \geq 28$ (total combined offensive capability rating from engineer platoons and reconnaissance troops)
- $12x_0 + 3x_1 + 14x_2 \geq 55$ (total combined offensive capability rating from all)
- $4x_0 + x_2 \leq 86$ (total combined deployment weight of engineer platoons and CBRN platoons)
- $4x_0 + 6x_1 \leq 89$ (total deployment weight of engineer platoons and reconnaissance troops)
- $4x_0 + 6x_1 + x_2 \leq 97$ (total combined deployment weight of all)
- $3x_1 + 14x_2 \leq 186$ (total combined offensive capability rating from reconnaissance troops and CBRN platoons)
- $12x_0 + 3x_1 + 14x_2 \leq 186$ (total combined offensive capability rating from all)
- $9x_0 + 8x_1 \leq 112$ (total fuel demand of engineer platoons and reconnaissance troops)
- $8x_1 + 2x_2 \leq 155$ (total fuel demand of reconnaissance troops and CBRN platoons)
- $9x_0 + 2x_2 \leq 85$ (total fuel demand of engineer platoons and CBRN platoons)
- $9x_0 + 8x_1 + 2x_2 \leq 85$ (total fuel demand of all)
- $7x_1 + 4x_2 \leq 40$ (total combined mobility rating from reconnaissance troops and CBRN platoons)
- $8x_0 + 7x_1 + 4x_2 \leq 101$ (total combined mobility rating from all)

## 5: Define the symbolic representation of the problem
```json
{
    'sym_variables': [('x0', 'engineer platoons'), ('x1', 'reconnaissance troops'), ('x2', 'CBRN platoons')],
    'objective_function': '3*x0 + 7*x1 + 6*x2',
    'constraints': [
        '4*x0 + 6*x1 + x2 >= 40',
        '12*x0 + 14*x2 >= 30',
        '12*x0 + 3*x1 >= 28',
        '12*x0 + 3*x1 + 14*x2 >= 55',
        '4*x0 + x2 <= 86',
        '4*x0 + 6*x1 <= 89',
        '4*x0 + 6*x1 + x2 <= 97',
        '3*x1 + 14*x2 <= 186',
        '12*x0 + 3*x1 + 14*x2 <= 186',
        '9*x0 + 8*x1 <= 112',
        '8*x1 + 2*x2 <= 155',
        '9*x0 + 2*x2 <= 85',
        '9*x0 + 8*x1 + 2*x2 <= 85',
        '7*x1 + 4*x2 <= 40',
        '8*x0 + 7*x1 + 4*x2 <= 101'
    ]
}
```

## Step 6: Implement the optimization problem using Gurobi
```python
import gurobi

# Create a new model
model = gurobi.Model()

# Define the variables
x0 = model.addVar(name="engineer_platoons", vtype=gurobi.GRB.INTEGER)
x1 = model.addVar(name="reconnaissance_troops", vtype=gurobi.GRB.INTEGER)
x2 = model.addVar(name="CBRN_platoons", vtype=gurobi.GRB.INTEGER)

# Define the objective function
model.setObjective(3*x0 + 7*x1 + 6*x2, gurobi.GRB.MAXIMIZE)

# Add constraints
model.addConstr(4*x0 + 6*x1 + x2 >= 40)
model.addConstr(12*x0 + 14*x2 >= 30)
model.addConstr(12*x0 + 3*x1 >= 28)
model.addConstr(12*x0 + 3*x1 + 14*x2 >= 55)
model.addConstr(4*x0 + x2 <= 86)
model.addConstr(4*x0 + 6*x1 <= 89)
model.addConstr(4*x0 + 6*x1 + x2 <= 97)
model.addConstr(3*x1 + 14*x2 <= 186)
model.addConstr(12*x0 + 3*x1 + 14*x2 <= 186)
model.addConstr(9*x0 + 8*x1 <= 112)
model.addConstr(8*x1 + 2*x2 <= 155)
model.addConstr(9*x0 + 2*x2 <= 85)
model.addConstr(9*x0 + 8*x1 + 2*x2 <= 85)
model.addConstr(7*x1 + 4*x2 <= 40)
model.addConstr(8*x0 + 7*x1 + 4*x2 <= 101)

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objval)
    print("Engineer platoons: ", x0.varValue)
    print("Reconnaissance troops: ", x1.varValue)
    print("CBRN platoons: ", x2.varValue)
else:
    print("The model is infeasible")
```