![]() The tier of the selected skyscraper is replaced with the value that yields the highest global population, and the process is then repeated again. For each tier the global population is computed. The idea is the following: a skyscraper is randomly selected in the layout and its tier is varied between 1 and 5. In order to build my own program, I used a randomized approach. So obviously this kind of algorithm cannot be used to optimize a 100+ houses layout. To help you understand how huge it is, for 30 houses this represents approximately 1021 combinations! And 30 houses is really small in an Anno 1800 game. ![]() But its main drawback is the computing time: as each skyscraper can have 5 tier values, using a layout with n houses makes the algorithm generate 5n combinations. ![]() The strength of this brute force algorithm is that it yields an exact solution: the population it returns actually is the highest you can get for the given layout. Given a layout, the algorithm generates every possible combination of tiers and computes its global population. Its idea is quite simple: every skyscraper can have a tier between 1 and 5. The only other skyscraper population optimization program I found was a brute force algorithm. I consider here that you know how all of this works in game, if you don’t just check the in game help by clicking the question mark on the upper left corner of a skyscraper interface. What principles does the program rely on? An example of this critical thinking is given in figure … and detailed in section … of the Advanced program understanding section. So before you apply the layout to your game, think about it, especially for low tier skyscrapers: is it possible to increase their tier without messing up with the solution.
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