Making a script computationally feasible

My script calculates the electricity consumption of households and EVs.

I have 400 EVs and 36 households. The issue is that I will get a very large number of combinations, I need to somehow sample my data to be able to handle it.

For each combination of vehicle and household, there will be an I-value, denoting how much the electricity consumption increases. Each household will have a matrix

with I-values, denoting all possible combinations of EVs. All these are stored in a cell array. If every household has one vehicle, the number of possible combinations are 4.7223664828e+93.

How can I overcome this?

Answer 1

[Steven Lord]

What is your end goal? Is it to assign 36 of the electric vehicles to the 36 households, one per household, to minimize the energy consumption? If so see the matchpairs function.

Is it to partition the list of electric vehicles into 36 sets, one per household, such that the total consumption is minimized?

Or is it something else? If so please explain your goal in more detail.

[Joel Schelander]

Sorry I meant power demand, not elextricity consumption.

If a household has three or more inhabitants, the house can have two vehicles. My goal is to plot how the maximum power demand of a household changes with an EV introduction:

I=max(Hconsumption+EVconsumption)/max(Hconsumption)

So since I will have so many I-values, I need to resample them somehow, to make the script computationally feasible.