MacGregor and Ormerod demonstrated that nonboundary points were the most important metric in having humans solve this problem, while one of the best implementations of a solution to its symmetric version is named Concorde. In APX, Christofide's algorithm can approximate versions of this problem that satisfy the triangle (*) inequality, and most solutions to this problem have made use of cutting planes. One non-optimal solution to this problem repeatedly checks for the lightest edge to a non-visited node and is called the nearest neighbor algorithm. Dealing with a method to find optimal tours, for 10 points, name this NP-complete problem whose
MacGregor and Ormerod demonstrated that nonboundary points were the most important metric in having humans solve this problem, while one of the best implementations of a solution to its symmetric version is named Concorde. In APX, Christofide's algorithm can approximate versions of this problem that satisfy the triangle (*) inequality, and most solutions to this problem have made use of cutting planes. One non-optimal solution to this problem repeatedly checks for the lightest edge to a non-visited node and is called the nearest neighbor algorithm. Dealing with a method to find optimal tours, for 10 points, name this NP-complete problem whose namesake entrepreneur needs to minimize the cost of visiting cities.
MacGregor and Ormerod demonstrated that nonboundary points were the most important metric in having humans solve this problem, while one of the best implementations of a solution to its symmetric version is named Concorde.
{traveling salesman} problem [or {TSP}]