The one dimensional cutting stock problem is a special case of it and Applegate and Bixby designed the CONCORDE program to solve it. A 3/2 approximative algorithm to solve it is the Christofides algorithm. One heuristic often used for it is a generalization of the 2-opt and 3-opt methods, the (*) Lin-Kernighan algorithm. Sometimes simplified by requiring the triangle inequality, it's inefficiently solved by the nearest neighbor algorithm, and it's equivalent to finding the Hamiltonian cycle with
The one dimensional cutting stock problem is a special case of it and Applegate and Bixby designed the CONCORDE program to solve it. A 3/2 approximative algorithm to solve it is the Christofides algorithm. One heuristic often used for it is a generalization of the 2-opt and 3-opt methods, the (*) Lin-Kernighan algorithm. Sometimes simplified by requiring the triangle inequality, it's inefficiently solved by the nearest neighbor algorithm, and it's equivalent to finding the Hamiltonian cycle with least weight given a complete weighted graph. For 10 points, name this NP-hard problem of finding the least cost round trip if a namesake merchant visits each city once.
The one dimensional cutting stock problem is a special case of it and Applegate and Bixby designed the CONCORDE program to solve it.
{Traveling Salesman} problem (or {TSP})