## Problem Description and Formulation

The problem is an optimization problem where we need to maximize an objective function subject to several constraints. The objective function is to maximize \(8s + 5k + 8c + 9st + 5ki\), where \(s\), \(k\), \(c\), \(st\), and \(ki\) represent the quantities of sashimi, kale salads, corn cobs, steaks, and kiwis, respectively.

The constraints are as follows:
1. The total calcium from all food items cannot exceed 176 milligrams.
2. The calcium content of each food item is given: sashimi (\(r0: 17mg\)), kale salads (\(r0: 26mg\)), corn cobs (\(r0: 2mg\)), steaks (\(r0: 5mg\)), and kiwis (\(r0: 1mg\)).
3. At least 32 milligrams of calcium must come from kale salads, steaks, and kiwis.
4. At most 81 milligrams of calcium can come from corn cobs and steaks.
5. No more than 48 milligrams of calcium can come from sashimi and kiwis.
6. At most 110 milligrams of calcium can come from sashimi, corn cobs, and kiwis.
7. The total calcium intake from all sources cannot exceed 176 milligrams.
8. All variables can take fractional values.

## Gurobi Code Formulation

```python
import gurobi as gp

# Define the model
m = gp.Model("calcium_optimization")

# Define the variables
sashimi = m.addVar(name="sashimi", lb=0)  # lower bound 0, can be fractional
kale_salads = m.addVar(name="kale_salads", lb=0)  # lower bound 0, can be fractional
corn_cobs = m.addVar(name="corn_cobs", lb=0)  # lower bound 0, can be fractional
steaks = m.addVar(name="steaks", lb=0)  # lower bound 0, can be fractional
kiwis = m.addVar(name="kiwis", lb=0)  # lower bound 0, can be fractional

# Objective function: maximize 8s + 5k + 8c + 9st + 5ki
m.setObjective(8 * sashimi + 5 * kale_salads + 8 * corn_cobs + 9 * steaks + 5 * kiwis, gp.GRB.MAXIMIZE)

# Constraints
# Total calcium constraint
m.addConstr(17 * sashimi + 26 * kale_salads + 2 * corn_cobs + 5 * steaks + 1 * kiwis <= 176, "total_calcium")

# Calcium from kale salads, steaks, and kiwis >= 32
m.addConstr(26 * kale_salads + 5 * steaks + 1 * kiwis >= 32, "min_calcium_from_kst_ki")

# Calcium from corn cobs and steaks <= 81
m.addConstr(2 * corn_cobs + 5 * steaks <= 81, "max_calcium_from_cst")

# Calcium from sashimi and kiwis <= 48
m.addConstr(17 * sashimi + 1 * kiwis <= 48, "max_calcium_from_ski")

# Calcium from sashimi, corn cobs, and kiwis <= 110
m.addConstr(17 * sashimi + 2 * corn_cobs + 1 * kiwis <= 110, "max_calcium_from_sck_ki")

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Sashimi: ", sashimi.x)
    print("Kale Salads: ", kale_salads.x)
    print("Corn Cobs: ", corn_cobs.x)
    print("Steaks: ", steaks.x)
    print("Kiwis: ", kiwis.x)
else:
    print("The model is infeasible")
```