A simulation based heuristic approach to a resource investment problem (RIP)

Abstract

A simulation-based heuristic approach is presented for a resource investment problem (RIP). This version of the RIP considers the trade-off between the number of resources, project makespan and resource utilization. A win-win goal is a reduction in project makespan while improving resource utilization. The RIP heuristic is presented as an executive for RCAN, a simulation tool that produces solutions to the multi-mode resource constrained project scheduling problem (RCPSP). The RIP heuristic uses feedback from RCAN to iteratively modify a set of renewable resources. The heuristic is shown to be effective on real-world, large-scale depot maintenance projects. In addition, the simulation tool uses a priority rule approach to schedule project tasks for the RCPSP problem. Therefore the RCPSP priority rule has a major effect on the RIP heuristic. An analysis is presented showing how various priority rules impact the RIP heuristic's ability to reduce the makespan while maintaining or increasing resource utilization.