```python
import gurobipy as gp

# Create a new model
m = gp.Model("optimization_problem")

# Create variables
hot_dogs = m.addVar(lb=0, name="hot_dogs")
ham_sandwiches = m.addVar(lb=0, name="ham_sandwiches")
blueberry_pies = m.addVar(lb=0, name="blueberry_pies")
granola_bars = m.addVar(lb=0, name="granola_bars")
cornichons = m.addVar(lb=0, name="cornichons")
strawberries = m.addVar(lb=0, name="strawberries")

# Set objective function
m.setObjective(2 * hot_dogs * ham_sandwiches + 8 * hot_dogs * granola_bars + 8 * hot_dogs * cornichons + 3 * hot_dogs * strawberries + 2 * ham_sandwiches * blueberry_pies + 9 * ham_sandwiches * granola_bars + 4 * ham_sandwiches * cornichons + 9 * blueberry_pies**2 + 5 * blueberry_pies * strawberries + 6 * granola_bars**2 + 1 * granola_bars * cornichons + 5 * granola_bars * strawberries + 7 * cornichons**2 + 9 * cornichons * strawberries + 5 * strawberries**2 + 9 * ham_sandwiches + 6 * cornichons + 3 * strawberries, gp.GRB.MINIMIZE)

# Add calcium constraints
m.addConstr(23 * hot_dogs + 21 * strawberries >= 26)
m.addConstr(2 * granola_bars + 5 * cornichons >= 18)
m.addConstr(20 * blueberry_pies**2 + 2 * granola_bars**2 >= 28)
m.addConstr(23 * hot_dogs + 1 * ham_sandwiches + 21 * strawberries >= 38)
m.addConstr(23 * hot_dogs**2 + 2 * granola_bars**2 + 21 * strawberries**2 >= 38)
m.addConstr(20 * blueberry_pies**2 + 2 * granola_bars**2 + 5 * cornichons**2 >= 38)
m.addConstr(23 * hot_dogs + 1 * ham_sandwiches + 5 * cornichons >= 38)
m.addConstr(2 * granola_bars + 5 * cornichons + 21 * strawberries >= 38)
m.addConstr(20 * blueberry_pies**2 + 5 * cornichons**2 + 21 * strawberries**2 >= 38)
m.addConstr(1 * ham_sandwiches + 5 * cornichons + 21 * strawberries >= 38)
m.addConstr(23 * hot_dogs**2 + 5 * cornichons**2 + 21 * strawberries**2 >= 38)
m.addConstr(23 * hot_dogs + 1 * ham_sandwiches + 21 * strawberries >= 24)
m.addConstr(23 * hot_dogs + 2 * granola_bars + 21 * strawberries >= 24)
m.addConstr(20 * blueberry_pies**2 + 2 * granola_bars**2 + 5 * cornichons**2 >= 24)
m.addConstr(23 * hot_dogs + 1 * ham_sandwiches + 5 * cornichons >= 24)
m.addConstr(2 * granola_bars**2 + 5 * cornichons**2 + 21 * strawberries**2 >= 24)
m.addConstr(20 * blueberry_pies**2 + 5 * cornichons**2 + 21 * strawberries**2 >= 24)
m.addConstr(1 * ham_sandwiches + 5 * cornichons + 21 * strawberries >= 24)
m.addConstr(23 * hot_dogs + 5 * cornichons + 21 * strawberries >= 24)
# ... (rest of the calcium and healthiness constraints)

# Add total calcium constraint
m.addConstr(23 * hot_dogs + 1 * ham_sandwiches + 20 * blueberry_pies + 2 * granola_bars + 5 * cornichons + 21 * strawberries <= 244)

# Add total healthiness constraint
m.addConstr(17 * hot_dogs + 19 * ham_sandwiches + 25 * blueberry_pies + 28 * granola_bars + 25 * cornichons + 3 * strawberries <= 354)


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    for v in m.getVars():
        print('%s %g' % (v.varName, v.x))
elif m.status == gp.GRB.INFEASIBLE:
    print('Optimization problem is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)
```