  The Multiprocessor Scheduling Problem (MSP) is an NP-Complete problem with
significant applications in computer and operations systems. We provide a
survey of the wide array of polynomial-time approximation, heuristic, and
meta-heuristic based algorithms that exist for solving MSP. We also implement
Fujita's state-of-the-art Branch-and-Bound algorithm and evaluate the benefit
of using Fujita's binary search bounding method instead of the Fernandez bound.
We find that in fact Fujita's method does not offer any improvement over the
Fernandez bound on our data set.
