Decision variables of case study
Continue the case study of the Capacitated Plant Location model of a car manufacture. You are given four Pandas data frames demand, var_cost, fix_cost, and cap containing the regional demand (thous. of cars), variable production costs (thous. $US), fixed production costs (thous. $US), and production capacity (thous. of cars). All these variables have been printed to the console for your viewing.
Latihan ini adalah bagian dari kursus
Supply Chain Analytics in Python
Petunjuk latihan
- Initialize the class.
- Define the decision variables using
LpVariable.dictsand python's list comprehension.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Initialize Class
model = LpProblem("Capacitated Plant Location Model", ____)
# Define Decision Variables
loc = ['USA', 'Germany', 'Japan', 'Brazil', 'India']
size = ['Low_Cap','High_Cap']
x = LpVariable.dicts("production_",
[(i,j) for ____ in ____ for ____ in ____],
lowBound=____, upBound=____, cat=_____)
y = LpVariable.dicts("plant_",
[____ for ____ in ____ for ____ in ____], cat=____)