Table 1.4 Optimum results of the ordering processes.
|
||||
---|---|---|---|---|
x | 0 | 1 | 2 | 3 |
f(x) | 10.99 | 7.9 | 15.46 | 16.93 |
Table 1.5 Optimum results of the number of integer cycles.
N | ||||
---|---|---|---|---|
x | 0 | 1 | 2 | 3 |
f(x) | 2.60 | 3.66 | 1.34 | 1.9 |
Table 1.6 Optimum results of the effective lead time.
LE | ||||
---|---|---|---|---|
x | 0 | 1 | 2 | 3 |
f(x) | -0.03 | -0.012 | 0.04 | -0.039 |
Table 1.7 Optimal solution of the TCU(Y).
TCU(y) | ||||
---|---|---|---|---|
x | 0 | 1 | 2 | 3 |
f(x) | 17.32 | 12.25 | 49.19 | 69.57 |
Table 1.8 Optimum results of the reorder in Le D.
Le D | ||||
---|---|---|---|---|
x | 0 | 1 | 2 | 3 |
f(x) | -0.9 | -0.36 | 1.6 | -0.78 |
Table 1.9 The optimal results of the inventory in trapezoidal rule.
Parameters | T*0 | N | LE | TCU(y) | Le d |
---|---|---|---|---|---|
x | 0 | 1 | 2 | 3 | 4 |
|
37.32 | 7.73 | -0.038 | 37.36 | -2.01 |
Figure 1.3 Trapezoidal rule in brownian movement.
It became accepted that there might be no time along requesting and buying of materials. The ascertaining Reorder level includes the figuring of utilization cost every day. Consider an association that works with a provider. The organization stores a few items renew by the providers to fulfil its Customers need.
Figure 1.3. Depicts the applicable of Inventories of Parameters Y ∗, T0, N, LE, TCU(Y), Le d calculation and the subsequent optimization of Inventories with the aim of minimizing the proposed goal.
1.4.1 Numerical Examples
This Numerical Example to illustrate the above Mathematical model.
Parameters 1: k1 = $105, H = $.06, d = 29 units per day L = 29 days. Optimal solutions Y* = 346.41,
Parameters 2: k1 = $52, H = $.04, d = 20 units per day L = 29 days. Optimal solutions Y* = 228.04,
Parameters 3: k1 = $98, H = $.02, d = 41 units per day L = 29 days. Optimal solutions Y* = 633.88,
Parameters 4: k1 = $104, H = $.03, d=22 units per day L = 29 days. Optimal solutions Y* = 372.38,