To solve this optimization problem using Gurobi, we will first import the necessary libraries and define our variables. We'll then set up our objective function and constraints according to the problem description.

```python
from gurobipy import *

# Create a model
m = Model("Optimization_Problem")

# Define variables
sashimi = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="sashimi")
kale_salads = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="kale_salads")
chicken_thighs = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="chicken_thighs")
protein_bars = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="protein_bars")
hot_dogs = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="hot_dogs")
bagged_salads = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="bagged_salads")

# Objective function
m.setObjective(4.42*sashimi + 1.83*kale_salads + 7.55*chicken_thighs + 7.94*protein_bars + 5.31*hot_dogs + 9.47*bagged_salads, GRB.MINIMIZE)

# Constraints
m.addConstr(11*sashimi + 19*kale_salads + 9*chicken_thighs + 13*protein_bars + 3*hot_dogs + 3*bagged_salads <= 693, "cost_constraint")
m.addConstr(18*sashimi + 21*kale_salads + 17*chicken_thighs + 0*protein_bars + 6*hot_dogs + 0*bagged_salads <= 836, "sourness_constraint")

# Additional constraints
m.addConstr(kale_salads + chicken_thighs >= 45)
m.addConstr(sashimi - 2*kale_salads <= 10)
m.addConstr(8*sashimi - 5*kale_salads >= 0)
m.addConstr(-6*chicken_thighs + 3*bagged_salads >= 0)
m.addConstr(-8*sashimi + 5*kale_salads >= 0)
m.addConstr(minus_8_times_chicken_thighs_plus_six_times_hot_dogs := -8*chicken_thighs + 6*hot_dogs, GRB.CONTINUOUS)
m.addConstr(minus_8_times_chicken_thighs_plus_six_times_hot_dogs >= 0)

# Sourness constraints
m.addConstr(18*sashimi + 21*kale_salads + 17*chicken_thighs <= 836, "max_sourness")
m.addConstr(6*hot_dogs + 0*bagged_salads <= 412, "hot_dog_bagged_max_sourness")
m.addConstr((0*protein_bars) + (6*hot_dogs) <= 460, "protein_hot_dog_max_sourness")

# Optimize the model
m.optimize()
```