test

.config/Code/User/History/7bdc530f/H9qU

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+import numpy as np
+from scipy.optimize import minimize
+import matplotlib.pyplot as plt
+
+def m(x):
+    # Material used for packaging
+    return np.sum(x * np.array([3, 2, 4]))
+
+def optimize_box(W_b):
+    # Initial guess for fractions x
+    x0 = np.ones(3) / 3
+
+    # Define the objective function
+    def obj(x):
+        return -m(x)
+
+    # Define the constraints
+    cons = ({'type': 'ineq', 'fun': lambda x: W_b - np.sum(x * np.array([3, 2, 4]))},
+            {'type': 'ineq', 'fun': lambda x: x})
+
+    # Minimize the objective function
+    res = minimize(obj, x0, method='SLSQP', constraints=cons)
+
+    return res.x
+
+# Example values
+W_b = 15  # box weight capacity
+
+x_opt = optimize_box(W_b)
+
+print("Optimal fractions:", x_opt)
+print("Minimum material used:", m(x_opt))
+
+# Plotting the graph
+labels = ['Item X', 'Item Y', 'Item Z']
+plt.bar(labels, x_opt, color='skyblue')
+plt.xlabel('Items')
+plt.ylabel('Fraction in the Box')
+plt.title('Optimal Fractions of Items Packed into the Box')
+plt.show()