branch-and-bound algorithms

Branch-and-bound is a method used to solve complex decision problems, such as finding the best way to schedule tasks or minimize costs. It systematically explores options by dividing the problem into smaller parts (branches). For each part, it calculates a bound indicating the best possible outcome achievable within that subset. If this bound is worse than the current best solution, the algorithm disregards that branch, saving time. By intelligently pruning unlikely options, branch-and-bound efficiently narrows down to the optimal solution without exhaustively checking every possibility.