Scheduling resource-constrained projects using branch and bound and parallel computing techniques

Based on the idea of dividing the task into several processes, we centre our interest on the techniques provided by parallel computing to solve the resource-constrained project scheduling problem, with the objective of obtaining a feasible schedule for the activities that minimises the length of the total project. The scheme that leads to the best results performs a static first-level decomposition of the solution tree, where processes search for a compromise between the benefits obtained after a parallel search and the communication and coordination costs implied. The contribution of the concept of safe cutsets has allowed the cutset dominance rule to be applied in a parallel implementation. Similar considerations will have to be taken into account when solving other problems, by designing parallel branch and bound algorithms which use dominance rules that are only applicable when performing a depth-first search.