This is a replication, in Python, of the discrete event simulation given by Law and Kelton (2000) for a single-product inventory system (s,S), previously written in FORTRAN (p. 66) and in C (p. 73).
Note that Law and Kelton run a single replication, as does this Python replication, and thus the output will differ some between the simulations due, for instance, to the use of different random number streams.
Policy Average total cost Average ordering cost Average holding cost Average shortage cost
( 20, 40) 126.61 99.26 9.25 18.10
( 20, 60) 122.74 90.52 17.39 14.83
( 20, 80) 123.86 87.36 26.24 10.26
( 20,100) 125.32 81.37 36.00 7.95
( 40, 60) 126.37 98.43 25.99 1.95
( 40, 80) 125.46 88.40 35.92 1.14
( 40,100) 132.34 84.62 46.42 1.30
( 60, 80) 150.02 105.69 44.02 0.31
( 60,100) 143.20 89.05 53.91 0.24
Policy Average total cost Average ordering cost Average holding cost Average shortage cost
( 20, 40) 126.87 97.36 8.61 20.90
( 20, 60) 124.72 92.13 15.87 16.71
( 20, 80) 128.44 90.36 24.19 13.89
( 20,100) 126.37 81.82 37.24 7.31
( 40, 60) 125.92 99.18 25.16 1.57
( 40, 80) 120.65 85.70 34.55 0.39
( 40,100) 131.16 85.11 45.76 0.29
( 60, 80) 138.88 92.85 45.96 0.07
( 60,100) 145.83 88.98 56.85 0.00