4 Multi Objective Optimization

The scope of this analysis is to minimise the construction and maintenance cost and keep the duration of a not operating airport due to maintenance as low as possible.

Our airport system provides facilities for the biggest and heaviest privat operating airplanes on the markt. Our goal was it to minimise the total operating cost for the airport system over its whole lifetime of 100 yrs.

In this optimisation we will draw our focus to the lowest CO2 Emission, Energy and Costs over life time for the two systems we chose in our LCA.

As for the total number of interruptions and the maximum distance between interventions, we have taken into account a large set of variables that play a role in our analysis.

As for the total number of interruptions and the maximum distance between interventions, we have taken into account a large set of variables to describe our System as best as possible.

For take off and landing the two biggest privat operating airplanes on the market (Boeing 747 and Airbus 380) require a width of the runway of min. 60m and a length of min. 2000m.
Both airplanes are similar height and size, therefore the hangars smallest size is limited.

The  parameters of the fitness functions point out the different maintenance actions, the production of emission, total costs (incl. Construction and Maintenance) during lifetime and the pareto function (shown below), which optimally state is an allocation of researches from which it is impossible to reallocate so as to make any preference better off without making at least one individual or preference criterion worse off.

We defined the hangar size and the length of the runway as a range of variable parameters and 20 frames with 40 footings and a runway width of 60 meters as static parameters. We calculated our fitness function with a generation of 25 and a populationsize of 80.

W = width

H = height

maxH = ridge height

runL = runway length

 

Steel Frame + PCC Runway

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Timber Frame + HMA Runway

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