An Enhanced Branch-and-bound Algorithm for the Talent Scheduling Problem
  The talent scheduling problem is a simplified version of the real-world film
shooting problem, which aims to determine a shooting sequence so as to minimize
the total cost of the actors involved. In this article, we first formulate the
problem as an integer linear programming model. Next, we devise a
branch-and-bound algorithm to solve the problem. The branch-and-bound algorithm
is enhanced by several accelerating techniques, including preprocessing,
dominance rules and caching search states. Extensive experiments over two sets
of benchmark instances suggest that our algorithm is superior to the current
best exact algorithm. Finally, the impacts of different parameter settings are
disclosed by some additional experiments.
