I have a table of a 18,000 billboards with an ID, latitude, longitude, Impacts(the amount of people that see the billboard in a month).
| ID | Latitude | Longitude | Impacts |
|---|---|---|---|
| 1 | 107.45 | 92.45 | 200,000 |
| 2 | 102.67 | 96.67 | 180,000 |
| 3 | 105.12 | 94.23 | 160,000 |
| 4 | 106.42 | 91.87 | 220,000 |
| 5 | 109.89 | 93.56 | 240,000 |
The idea is I want to build a model that optimizes for a maximum amount of impacts, keeping a minimum distance between each billboard, for an amount of billboards chosen by the user.
I can build a matrix with the linear distances of each billboard to all the others, so basically I have the value that I want to maximize which are the impacts, a distance matrix which has linear distances between each billboard which is a constraint and the amount of billboards to select which is another constraint.
does anyone know a sort of linear programming model that I could implement for this specific case?
