Mon Apr 14 09:59:50 2025

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

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

  Weight limit is  170
  Number of items is  7
  Number of subsets is  128
  Value array  [442. 525. 511. 593. 546. 564. 617.]
  Weight array  [41. 50. 49. 59. 55. 57. 60.]

  Selected items: [0 0 1 1 0 0 1]
  Weight  168.0
  Value  1721.0
  Ratio  10.244047619047619

  Selected items: [0 1 0 0 0 1 1]
  Weight  167.0
  Value  1706.0
  Ratio  10.215568862275449

  Selected items: [1 0 0 1 1 0 0]
  Weight  155.0
  Value  1581.0
  Ratio  10.2

  Selected items: [0 0 1 1 1 0 0]
  Weight  163.0
  Value  1650.0
  Ratio  10.122699386503067

  Selected items: [0 1 0 0 0 1 1]
  Weight  167.0
  Value  1706.0
  Ratio  10.215568862275449

  Selected items: [1 0 0 0 0 1 1]
  Weight  158.0
  Value  1623.0
  Ratio  10.272151898734178

  Selected items: [0 1 1 0 0 1 0]
  Weight  156.0
  Value  1600.0
  Ratio  10.256410256410257

  Selected items: [0 1 0 0 0 1 1]
  Weight  167.0
  Value  1706.0
  Ratio  10.215568862275449

  Selected items: [0 1 0 1 1 0 0]
  Weight  164.0
  Value  1664.0
  Ratio  10.146341463414634

  Selected items: [1 0 1 0 1 0 0]
  Weight  145.0
  Value  1499.0
  Ratio  10.337931034482759

knapsack_random_test():
  Normal end of execution.
Mon Apr 14 09:59:50 2025