This paper proposes a new Evolutionary Algorithm for the Dynamic Resource Constrained Project Scheduling Problem.This algorithm has new features that get around some problems like premature convergence and other ones. The indirect representation approach was used because it allows the construction of a feasible solution from any input priorities. A parallel version is also proposed, making good use of multicore processors available nowadays. The results of sequential and parallel versions were very significant, improving in almost all ways the best results present in literature.
Dynamic Resource-Constrained Project Scheduling Problem (DRCPSP) is a scheduling problem that works with an uncommon kind of resources: the Dynamic Resources. They increase and decrease in quantity according to the activated tasks and are not bounded like other project scheduling problems. This paper presents a new mathematical formulation for DRCPSP as well as two hybrid heuristics merging an evolutionary algorithm with an exact approach. Computational results show that both hybrid heuristics present better results than the stateof-the-art algorithm for DRCPSP does. The proposed formulation also provides better bounds.
In this paper, we present a variant of classical scheduling problems which deal with restricted resources. Unlike other models studied in the literature, the proposed model has no upper bound for the amount of available resources. The objective of this variant is to find a solution that maximises this amount at the end of the planning horizon. A hybrid evolutionary algorithm is proposed for this problem presenting very promising computational results.
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