Wed Oct  8 07:59:41 2025

knapsack_random_test():
  python version: 3.10.12
  numpy version:  1.26.4
  Test knapsack_random()

subset_random_test():
  Test subset_random()

  Subsets will be of size n =  5

31 : [1 1 1 1 1]
0 : [0 0 0 0 0]
29 : [1 1 1 0 1]
26 : [1 1 0 1 0]
24 : [1 1 0 0 0]
8 : [0 1 0 0 0]
2 : [0 0 0 1 0]
27 : [1 1 0 1 1]
21 : [1 0 1 0 1]
26 : [1 1 0 1 0]

knapsack_random_test01():
  knapsack_random() randomly selects a subset of n items
  and considers it as a solution to a knapsack problem.
  Maximize profit without exceeding weight limit.

  Number of items is  5
  Value array  [24 13 23 15 16]
  Weight array  [12  7 11  8  9]
  Weight limit is  26

  Selected items: [0 0 1 1 0]
  Weight  19
  Value  38
  Ratio  2.0

  Selected items: [1 1 1 0 1]
  Weight  39  exceeds weight limit  26

  Selected items: [0 1 0 1 1]
  Weight  24
  Value  44
  Ratio  1.8333333333333333

  Selected items: [1 0 0 0 1]
  Weight  21
  Value  40
  Ratio  1.9047619047619047

  Selected items: [0 1 1 0 1]
  Weight  27  exceeds weight limit  26

  Selected items: [1 0 1 0 0]
  Weight  23
  Value  47
  Ratio  2.0434782608695654

  Selected items: [1 0 1 0 0]
  Weight  23
  Value  47
  Ratio  2.0434782608695654

  Selected items: [0 0 0 1 0]
  Weight  8
  Value  15
  Ratio  1.875

  Selected items: [1 1 1 0 0]
  Weight  30  exceeds weight limit  26

  Selected items: [0 1 0 1 0]
  Weight  15
  Value  28
  Ratio  1.8666666666666667

knapsack_random_test():
  Normal end of execution.
Wed Oct  8 07:59:41 2025