Resource-constrained project scheduling with ant colony optimization algorithm - Niken A Savitri; I Nyoman Pujawan; Budi Santosa (Institut Teknologi Sepuluh Nopember (ITS), 2020)
Resource allocation commonly becomes one of the critical problems in project scheduling. This issue usually occursbecause project managers estimate the schedule of activities and network time without considering resource availability.Resource-Constrained Project Scheduling Problem (RCPSP) links to the allocation of resources or set of resources into certainactivities in order to accomplish particular objectives. Various approaches have been performed to overcome RCPSP, includingthe heuristic approach. In this research, Ant Colony Algorithm is used to solve RCPSP. There are 11 examples of projects beinginvestigated with dissimilarity in-network and several activities. The implementation of the Ant Colony Algorithm resulted inthe percentage of a near-optimal solution of 63.64%. Besides, the duration obtained from the algorithm above the manualscheduling (assumed optimal) was only 4.29%. Sensitivity analysis was performed to understand how substantially the changesof ACO parameters influenced the result obtained from the algorithm. Based on the result, it could be concluded that theparameters of ACO have no significant effect to project duration.