Efficient Branch-and-Bound Search

Combinatorial search algorithms are indispensable in many engineering applications, including manufacturing, scheduling, computer-aided design, and operations research. Finding the best approximate solution under given resource constraints is very important, especially for real-time applications. Traditional algorithms either require an impractical amount of time and space to find an optimal solution, or give heuristic solutions with no guarantee on their accuracy. This is not desirable in many critical real-time applications or when large problems are involved.

Research has been focused on studying resource-constrained discrete combinatorial optimization algorithms that find better solutions at the same cost, or algorithms that find solutions of the same quality but at a lower cost.