Initializing help system before first use

Results

The original problem description and instance data are taken from [GHP02] (Section 8.2 Production of drinking glasses). The costs and resource usage data for the six glass types are listed in Table Data for six glass types.

Table 2: Data for six glass types
Production cost Storage cost Initial stock Final stock Timeworker Timemachine Storage space
V1 100 25 50 10 3 2 4
V2 80 28 20 10 3 1 5
V3 110 25 0 10 3 4 5
V4 90 27 15 10 2 8 6
V5 200 10 0 10 4 11 4
V6 140 20 10 10 4 9 9

The solution of the original problem with the basic demand scenario has a total cost of € 185,899. The resulting detailed production plan is displayed in Table Optimal production plan for basic demand scenario. We find that the available manpower is fully used most of the time (in the first week, 351 hours are worked, in all other weeks the limit of 390 hours is reached) and the machines are used to their full capacity in certain time periods (weeks 1-3 and 5), but the available storage space is in excess of the actual needs.

Table 3: Optimal production plan for basic demand scenario
Week 1 2 3 4 5 6 7 8 9 10 11 12
V1 Prod. 8.8 5.5 0.6 30.2 27.4 8.6 23 20 29 30 28 42
Store 38.8 22.2 4.8 - 10.4 10
V2 Prod. 0 16 23 20 11 10 12 34 21 23 30 22
Store 3 10
V3 Prod. 18 35 17 10 9 21 23 15 10 0 13 27
Store 10
V4 Prod. 16 45 24 38 41 20 19 37 28 12 30 47
Store 10
V5 Prod. 47.7 14.6 35.1 14.3 23.5 22.8 43.8 0 26.5 2.8 0 0
Store 24.7 19.3 31.4 30.8 44.2 45 70.8 40.75 39.25 35 20 10
V6 Prod. 12 18 20 19 18 35 0.8 27.2 12 49 29.2 5.8
Store 0.75 19 27.25 10
Workers 351 390 390 390 390 390 390 390 390 390 390 390
Machines 850 850 850 753.2 850 836.8 790 675.2 742.5 650.2 641.2 641.8
Space 268.8 166.2 144.8 123 218.4 180 289.8 163 157 311 325.2 330

If we try to introduce robustness to such a tightly constrained problem, the outcome most likely will be 'problem infeasible' as there is no slack to incorporate alternatives. We have therefore somewhat relaxed the original bound on the personnel hours, assuming that its original value represents a rough worst-case estimate and that the actually available working hours are 20% higher. The more fine-grained estimate of absence results in the solution summarized in Table Summary results with robust formulation of absence. The overall cost of € 181,210 is slightly lower than the previous, fixed worst-case absence case.

Table 4: Summary results with robust formulation of absence
Week 1 2 3 4 5 6 7 8 9 10 11 12
Workers 243 378 370 407 325 398 383 414 412 445 429 437
CAPW-ABSENCE 437 437 429 429 414 398 398 414 445 445 429 437
Machines 609 850 736 770 736 794 772.2 739.8 803 839.5 734 747.5
Space 152.5 32 0 0 20 0 99 0 16 130 219.5 330

The scenario-based approach results in a higher total cost of €203,545. In the summary results in Table Summary results with demand scenarios we observe that both, machine capacity and workers' hours, are most of the time used at or close to their capacity limit (850 and 429=1.1·390 respectively). Furthermore, larger quantities of products are held in stock.

Table 5: Summary results with demand scenarios
Week 1 2 3 4 5 6 7 8 9 10 11 12
Workers 363 425 425 425 425 425 425 425 425 425 425 425
Machines 850 850 850 850 850 850 850 850 850 786.7 711 700.3
Space 230.7 145.9 150.4 126.3 233.2 211.9 306.8 181.7 169.7 256.7 305.7 330

For easier comparison, Table Summary results for deterministic model with 1.1CAPW shows the summary results for the original model with the same capacity limits as have been used wit the robust formulation in Table Summary results with demand scenarios, the total cost is in this case €181,432.

Table 6: Summary results for deterministic model with 1.1·CAPW
Week 1 2 3 4 5 6 7 8 9 10 11 12
Workers 243 378 370 407 305 418 393 425 425 425 425 425
Machines 609 850 736 770 681 849 799 771.2 840 783.2 721 721.5
Space 152.5 32 0 0 0 0 108.7 21.2 50.6 151.5 245.5 330


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