Efficient branch-and-bound algorithms on a two-level memory system

Branch-and-bound algorithms in a system with a two-level memory hierarchy were evaluated. An efficient implementation depends on the disparities in the numbers of subproblems expanded between the depth-first and best-first searches as well as the relative speeds of the main and secondary memories. A best-first search should be used when it expands a much smaller number of subproblems than that of a depth-first search, and the secondary memory is relatively slow. In contrast, a depth-first search should be used when the number of expanded subproblems is close to that of a best-first search. The choice is not as clear for cases in between these cases are studied. Two strategies are proposed and analyzed: a specialized virtual-memory system that matches the architectural design with the characteristics of the existing algorithm, and a modified branch-and-bound algorithm that can be tuned to the characteristic of the problem and the architecture. The latter strategy illustrates that designing a better algorithm is sometimes more effective that tuning the architecture alone