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# Untitled

a guest Mar 31st, 2020 71 Never
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1. import numpy
2. from binomialPoisson import *
3.
4. hugeNumber = float("inf")
5. unused = -1000
6.
7. stages = 10
8. seats = 50
9. fullFare = 500
10. discountFare = 250
11. costOccupied = 8
12.
13. meanFullDemand = numpy.array([unused,
14.                               1.3, 1.4, 1.9, 2.0, 2.2,
15.                               2.8, 2.2, 2.4, 1.8, 3.7])
16.
17. maxCanRelease = [unused, 10, 10, 10, 10, 10, 5, 5, 5, 5, 5]
18.
19.
20. f = numpy.zeros([stages+2, seats+1])
21. x = numpy.zeros([stages+1, seats+1], dtype=int)
22.
23. # Iterate through stages
24. for t in range(stages, 0, -1):
25.
26.     # Iterate through possible states (ie, number of seats occupied)
27.     for i in range(seats + 1):
28.
29.         demandProbability = poisson(meanFullDemand[t], seats)
30.
31.         value = -hugeNumber
32.         maxReleased = min(maxCanRelease[t], seats-i)
33.
34.         for p in range(maxReleased+1):
35.
36.             moveValue = -costOccupied*p + 250*p
37.
38.             seats_unoccupied = seats - i - p
39.
40.             for r in range(seats_unoccupied+1):
41.                 j = seats_unoccupied - r
42.                 moveValue += demandProbability[r]*(500*r + f[t+1, j])
43.
44.             if moveValue > value:
45.                 value = moveValue
46.                 bestMove = p
47.
48.         f[t, i] = value
49.         x[t, i] = bestMove
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