DASH: Dynamic Approach for Switching Heuristics

Complete tree search is a highly effective method for tackling MIP problems, and over the years, a plethora of branching heuristics have been introduced. Recently, portfolio algorithms have taken the process a step further, trying to predict the best heuristic for each instance at hand. This thesis identifies a method which decides the best time to switch the branching heuristic and it is shown how such\na system can be trained efficiently