A genetic hyperheuristic algorithm for the resource constrained project scheduling problem

The resource constrained project scheduling problem is one of the most important issues that project managers have to deal with during the project implementation, as constrained resource availabilities very often lead to delays in project completion and budget overruns. For solving this NP-hard optimization problem, we propose a genetic based hyperheuristic, i.e. an algorithm controlling a set of low-level heuristics which work in the solution domain. Chromosomes impose the sequence that the algorithm applies the low level heuristics. Implemented within a commercial project management software system, the hyperheuristic operates on the priority values that the software uses for scheduling activities. We perform a series of computational experiments with random generated projects. The results show that the algorithm is very promising for finding good solutions in reasonable time.