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

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

# Create variables
pasta = m.addVar(vtype=GRB.INTEGER, name="bowls_of_pasta")
cereal = m.addVar(vtype=GRB.CONTINUOUS, name="bowls_of_cereal")
chicken = m.addVar(vtype=GRB.INTEGER, name="rotisserie_chickens")
apples = m.addVar(vtype=GRB.INTEGER, name="apples")
corn = m.addVar(vtype=GRB.INTEGER, name="corn_cobs")
pie = m.addVar(vtype=GRB.INTEGER, name="blueberry_pies")

# Set objective function
m.setObjective(1.46*pasta**2 + 4.92*pasta*cereal + 1.71*pasta*chicken + 3.74*cereal*chicken + 2.27*cereal*apples + 3.68*cereal*corn + 9.9*cereal*pie + 4.54*chicken**2 + 5.5*chicken*apples + 5.58*chicken*corn + 9.16*apples**2 + 2.59*apples*corn + 9.65*apples*pie + 7.66*corn**2 + 9.4*pie**2 + 2.37*pasta + 4.73*cereal + 5.74*chicken + 7.68*apples + 4.96*pie, GRB.MINIMIZE)

# Add constraints based on resources/attributes
m.addConstr(8*pasta + 3*cereal + 5*chicken + 5*apples + 7*corn + 6*pie <= 90, "dollar_cost") # r0
m.addConstr(5*pasta + 1*cereal + 7*chicken + 7*apples + 5*corn + 8*pie <= 63, "umami_index") # r1
m.addConstr(5*pasta + 4*cereal + 4*chicken + 1*apples + 4*corn + 3*pie <= 85, "iron") # r2
m.addConstr(4*pasta + 6*cereal + 7*chicken + 7*apples + 6*corn + 2*pie <= 73, "tastiness") # r3


# Add other constraints
m.addConstr(3*cereal + 6*pie >= 5)
m.addConstr(8*pasta + 3*cereal >= 5)
m.addConstr(8*pasta + 7*corn >= 8)
m.addConstr(3*cereal + 5*apples + 6*pie >= 10)
m.addConstr(3*cereal**2 + 7*corn**2 + 6*pie**2 >= 10)
m.addConstr(8*pasta**2 + 3*cereal**2 + 5*apples**2 >= 10)
m.addConstr(5*chicken + 7*corn + 6*pie >= 10)
m.addConstr(8*pasta + 3*cereal + 5*chicken >= 10)
m.addConstr(3*cereal**2 + 5*chicken**2 + 5*apples**2 >= 10)
m.addConstr(8*pasta**2 + 5*chicken**2 + 5*apples**2 >= 10)
m.addConstr(3*cereal + 5*apples + 7*corn >= 10)
m.addConstr(3*cereal + 5*chicken + 6*pie >= 10)
m.addConstr(8*pasta + 5*chicken + 7*corn >= 10)
m.addConstr(5*chicken**2 + 5*apples**2 + 6*pie**2 >= 10)
m.addConstr(8*pasta + 5*chicken + 6*pie >= 10)
m.addConstr(3*cereal + 5*apples + 6*pie >= 13)
m.addConstr(3*cereal + 7*corn + 6*pie >= 13)
m.addConstr(8*pasta**2 + 3*cereal**2 + 5*apples**2 >= 13)
m.addConstr(5*chicken**2 + 7*corn**2 + 6*pie**2 >= 13)
m.addConstr(8*pasta + 3*cereal + 5*chicken >= 13)
m.addConstr(3*cereal + 5*chicken + 5*apples >= 13)
m.addConstr(8*pasta + 5*chicken + 5*apples >= 13)
m.addConstr(3*cereal + 5*apples + 7*corn >= 13)
m.addConstr(3*cereal + 5*chicken + 6*pie >= 13)
m.addConstr(8*pasta**2 + 5*chicken**2 + 7*corn**2 >= 13)
m.addConstr(5*chicken + 5*apples + 6*pie >= 13)
m.addConstr(8*pasta**2 + 5*chicken**2 + 6*pie**2 >= 13)
m.addConstr(3*cereal + 5*apples + 6*pie >= 13)
m.addConstr(3*cereal**2 + 7*corn**2 + 6*pie**2 >= 13)
m.addConstr(8*pasta + 3*cereal + 5*apples >= 13)
m.addConstr(5*chicken + 7*corn + 6*pie >= 13)


# ... (rest of the constraints)


# Optimize model
m.optimize()

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