Optimisation of ROI

The results of optimising the ROI are shown in Figure 16.1 (national level) and Figure 16.2 (European level) and are summarised in Table 16.2. [O c_nlo-1.xls, c_nlo-2.xls]

Note that by increasing the number of flight movements, the ROI has increased from 10% to 31% on the national level and from 16% to 38% for the European level. As a result however, the number of flight movements increased beyond a realistic market demand. This means that we have to specify

 Pilot run I t D f ROI [\$ billion] [hours] [km] [100 k] [%] National airport in North Sea 20.6 0.700 (0.650) 35.0 10.00 10 European airport in North Sea 36.6 1.05 (0.B50) 55.0 30.00 16

Numbers in italic represent optimised values.

When there is a slack, the values in the optimum solution are given between brackets.

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 A B C D E F G H I j -J" 1 Endogenous variables I t d f E 2 25 0.65 35 39.33333 7 866667 3 4 Objective function -1 -25 5 6 Maximum investment 1 25 =<= 25 7 Maximum time 1 0.65 <= 0.7 S Minimum distance 1 35 ->- 35 9 Minimum flight movements 1 39.33333 >- 10 10 Investment definition 1 -0.2 -0.15 12.1 = 12.1 11 Traveltime definition 1 -0.01 0.3 = 0.3 12 Exploitation revenues definition -0.2 1 0 - 0 13 14 Return on investment 31% 15 16 17 18 19 20 21 22 23 24 ► ir N i ► HIV WB! Status \Sheetl/Sheet2 / Sheet3 / <

Figure 16.1 Screenshot solved model (national airport)

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I

t

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1

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1

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Figure 16.2 Screenshot solved model (European airport)

 Pilot run I t D f ROI [\$ billion] [hours] [km] [100 k] [%] National airport in North Sea 25 0.650 35.0 39.33 S1 European airport in North Sea 45 0.850 55.0 86.00 SB

Numbers in italic represent optimised values.

When there is a slack, the values in the optimum solution are given between brackets.

 Pilot run I t D f ROI [\$ billion] [hours] [km] [100 k] [%] National airport in North Sea 21.35 0.650 35.0 15.00 14 European airport in North Sea 45 0.985 68.5 50.00 22

Numbers in italic represent optimised values.

When there is a slack, the values in the optimum solution are given between brackets.

an upper bound for the number of flight movements. Therefore, on a national level the market demand is restricted to 1 500 000 flight movements and on a European level to 5 000 000 flight movements.

The results of these simulations are summarised in Table 16.3. [O c_nlo-3.xls, c_nlo-4.xls]

Using a non-linear instead of a linear model results for the return on investment in an increase from 10% to 14% on the national level, and from 16% to 22% for the European level.

The interpretation of this is: the non-linear model takes into account economies of scale and yields an outcome according to the market demand to be expected. The linear model, by contrast, minimises the investment and, as a result, gives the smallest airport as an outcome.

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