so i have this program running on a spreadsheet that gives me reasonable results but the thing is that it maximizes the TOTAL VALUE of the function whereas what i actually want is to only maximize the TOTAL NUMBER of results of the function over a certain amount.
i dont care about the value once it reaches said amount, so i need some way to discard results under a certain threshold and find the maximun number of results over that threshold. this needs needs to be done within the algo itself so it keeps searching for a better combination.
the current function gives me reasonably good results but depending on data distribution i might get results with max objective function value but with a lower number of results over the theshold, whereas another result with lower objective value gives me more results over the threshold.
without getting into too many details theres this fantasy football game where i know the scores of all players for the last 2 seasons, each week a random game week is selected and scores are given to teams according to that weeks performance; teams above a certain threshold get a reward. so the idea is to find the lineup that gives you the higher number of weeks over the threshold, if you are below the threshold it doesnt matter the score, you lose.
my current model maximizes overall total score for all weeks and that is a reasonable approximation, but depending on how players synergize (or randomness) a team with a lower total weekly score might give you more wins.
is there any way to twist this models arm so it does what i want it to do? is this possible with other dedicated solvers? do i need to look into non linear programming to solve this?
i dont care about the value once it reaches said amount, so i need some way to discard results under a certain threshold and find the maximun number of results over that threshold. this needs needs to be done within the algo itself so it keeps searching for a better combination.
the current function gives me reasonably good results but depending on data distribution i might get results with max objective function value but with a lower number of results over the theshold, whereas another result with lower objective value gives me more results over the threshold.
without getting into too many details theres this fantasy football game where i know the scores of all players for the last 2 seasons, each week a random game week is selected and scores are given to teams according to that weeks performance; teams above a certain threshold get a reward. so the idea is to find the lineup that gives you the higher number of weeks over the threshold, if you are below the threshold it doesnt matter the score, you lose.
my current model maximizes overall total score for all weeks and that is a reasonable approximation, but depending on how players synergize (or randomness) a team with a lower total weekly score might give you more wins.
is there any way to twist this models arm so it does what i want it to do? is this possible with other dedicated solvers? do i need to look into non linear programming to solve this?
