A nature inspired metaheuristic for optimal leveling of resources in project management

Resource Leveling is a constrained problem with a large solution space, especially when the projects have numerous tasks. This makes the problem hard to tackle. In this study, a novel algorithm named sonar inspired optimization (SIO) belonging in Nature Inspired Intelligence is applied in both benchmark and artificial resource-leveling problems to investigate its performance. Results are compared to those derived from a Hybrid Genetic Algorithm (HGA) previously developed. Experimental findings show that the proposed algorithm is very promising as in most cases the obtained solutions prove superior or equally good to those of HGA and other competitive approaches. An additional approach of the proposed metaheuristic is that it generates only feasible solutions. The algorithm has been implemented in different programming languages so that in future applications will be user friendly for project managers.