In: Computer Science
Greedy algorithms.
Fractional Knapsack
n = 6
w = 20 pounds
| Item | Weight | Value | Value/Weight |
| 1 | 7 | 22 | 3.14 |
| 2 | 5 | 20 | 4 |
| 3 | 100 | 50 | 0.5 |
| 4 | 1 | 3 | 3 |
| 5 | 10 | 20 | 2 |
| 6 | 0.5 | 5 | 10 |
Sort all the items in decreasing order of their value / weight ratio
| I6 | I2 | I1 | I4 | I5 | I3 |
| 10 | 4 | 3.14 | 3 | 2 | 0.5 |
Construct a table with Remaining knapsack weight, Items in kanpsack and total profit obtained
| Knapsack Weight | Items in Knapsack | Profit |
| 20 | Ø | 0 |
| 19.5 | I6 | 5 |
| 14.5 | I6,I2 | 25 |
| 7.5 | I6,I2,I1 | 47 |
| 6.5 | I6,I2,I1,I4 | 50 |
| 0 | I6,I2,I1,I4,I5(6.5) | 50+(6.5*2) |
Maximum profit that can be gained is 63 by placing I6,I2,I1,I4 and 6.5 pounds of I5 in the knapsack.
Interval Scheduling
Set of jobs (si, fi) are as follows: (3, 6), (2, 4), (5, 9) (7, 10), (0, 9), (1, 3), (9, 11), and (6, 7)
| Job | Start Time | Finish Time |
| J1 | 3 | 6 |
| J2 | 2 | 4 |
| J3 | 5 | 9 |
| J4 | 7 | 10 |
| J5 | 0 | 9 |
| J6 | 1 | 3 |
| J7 | 9 | 11 |
| J8 | 6 | 7 |
Sort in the descending order of finish time
| Job | Start Time | Finish Time |
| J6 | 1 | 3 |
| J2 | 2 | 4 |
| J1 | 3 | 6 |
| J8 | 6 | 7 |
| J3 | 5 | 9 |
| J5 | 0 | 9 |
| J4 | 7 | 10 |
| J7 | 9 | 11 |
For each job, check if it is overlapping with the previous job i.e., starttime of current job is less than finish time of previous job
| Job | Start Time | Finish Time |
| J6 | 1 | 3 |
Next, (1,3) and (2,4) are overlapping as 2<3
| Job | Start Time | Finish Time |
| J6 | 1 | 3 |
| J1 | 3 | 6 |
| Job | Start Time | Finish Time |
| J6 | 1 | 3 |
| J1 | 3 | 6 |
| J8 | 6 | 7 |
Next, (6,7) and (5,9) are overlapping as 5<7
Next, (6,7) and (0,9) are overlapping as 0<7
| Job | Start Time | Finish Time |
| J6 | 1 | 3 |
| J1 | 3 | 6 |
| J8 | 6 | 7 |
| J4 | 7 | 10 |
Next, (7,10) and (9,11) are overlapping as 9<10
Hence, the intervals to be considered are (1,3)(3,6)(6,7)(7,10)
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