// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt /* This simple example shows how to call dlib's optimal linear assignment problem solver. It is an implementation of the famous Hungarian algorithm and is quite fast, operating in O(N^3) time. */ #include #include using namespace std; using namespace dlib; int main () { // Let's imagine you need to assign N people to N jobs. Additionally, each person will make // your company a certain amount of money at each job, but each person has different skills // so they are better at some jobs and worse at others. You would like to find the best way // to assign people to these jobs. In particular, you would like to maximize the amount of // money the group makes as a whole. This is an example of an assignment problem and is // what is solved by the max_cost_assignment() routine. // // So in this example, let's imagine we have 3 people and 3 jobs. We represent the amount of // money each person will produce at each job with a cost matrix. Each row corresponds to a // person and each column corresponds to a job. So for example, below we are saying that // person 0 will make $1 at job 0, $2 at job 1, and $6 at job 2. matrix cost(3,3); cost = 1, 2, 6, 5, 3, 6, 4, 5, 0; // To find out the best assignment of people to jobs we just need to call this function. std::vector assignment = max_cost_assignment(cost); // This prints optimal assignments: [2, 0, 1] which indicates that we should assign // the person from the first row of the cost matrix to job 2, the middle row person to // job 0, and the bottom row person to job 1. for (unsigned int i = 0; i < assignment.size(); i++) cout << assignment[i] << std::endl; // This prints optimal cost: 16.0 // which is correct since our optimal assignment is 6+5+5. cout << "optimal cost: " << assignment_cost(cost, assignment) << endl; }