[Solved] What will be the output of this code?from scipy.optimize import linprog c = [2, 3] A_eq = [[1, 1]] b_eq = [5] result = linprog(c, A_eq=A_eq, b_eq=b_eq, bounds=[(0, None), (0, None)]) print(result.x) | SciPy

SciPy - Advanced Optimization

What will be the output of this code?

from scipy.optimize import linprog
c = [2, 3]
A_eq = [[1, 1]]
b_eq = [5]
result = linprog(c, A_eq=A_eq, b_eq=b_eq, bounds=[(0, None), (0, None)])
print(result.x)

A[0. 5.]

B[2.5 2.5]

C[5. 0.]

D[0. 0.]

Step-by-Step Solution

Solution:

Step 1: Understand the problem constraints
The equality constraint is x1 + x2 = 5, with both variables >= 0.
Step 2: Minimize the objective function
The objective is to minimize 2*x1 + 3*x2. Since 3 > 2, minimizing cost means setting x2 as low as possible (0) and x1 as high as possible (5). So solution is x1=5, x2=0.
Final Answer:
[5. 0.] -> Option C
Quick Check:
linprog solution = [5. 0.] [OK]

Quick Trick: Minimize cost by assigning more to cheaper variable [OK]

Common Mistakes:

Swapping variable values
Ignoring bounds
Misinterpreting equality constraints

Master "Advanced Optimization" in SciPy

9 interactive learning modes - each teaches the same concept differently

Learn Why Deep Visual Try Challenge Project Recall Time

More SciPy Quizzes

What will be the output of this code?

Step 1: Understand the problem constraints

Step 2: Minimize the objective function

Final Answer:

Quick Check:

Want More Practice?