A priority rule heuristic for the multi-skilled resource-constrained project scheduling problem

Abstract

This research presents a priority rule heuristic approach for the multi-skilled resource-constrained project scheduling problem. The approach is based on a parallel schedule generation scheme which includes a new resource assignment procedure. The scheme combines three types of priority rules in order to schedule activities and assign resources to the skill requirements of these activities. In computational experiments, skill- and resource rule combinations are evaluated and selected based on two metrics using a Pareto Front approach. These rule combinations are then integrated with various activity priority rules after which their solution quality is evaluated. The heuristic approach and the selected rules are then employed to solve all project instances of the MSLIB dataset. It is shown that, on average, the presented approach is able to obtain solutions with a comparable quality to the solution quality of a meta-heuristic procedure from literature. Additionally, new best known solutions are obtained for the MSLIB dataset. The practical applicability of the heuristic is validated by solving empirical project instances.