Heuristics for Scheduling Resource-Constrained Projects: An Experimental Investigation

TLDR: This paper considers the project scheduling problem with multiple constrained resources and shows that the choice of priority rule is important with the parallel method, but with the sampling method, although it does affect the distribution of the sample, the choices of rule are not significant.

Abstract: This paper considers the project scheduling problem with multiple constrained resources. Two classes of heuristic procedure, both making use of priority rules, are discussed: the parallel method, which generates just one schedule; and the sampling method, which generates a set of schedules using probabilistic techniques and selects the best schedule from this sample. An experimental investigation is described in which a set of projects with different characteristics is scheduled by each of these heuristics with a variety of priority rules. The effects of the heuristic method, the project characteristics and the priority rules are assessed. It is shown that the choice of priority rule is important with the parallel method, but with the sampling method, although it does affect the distribution of the sample, the choice of rule is not significant. The sampling method with sample size 100 is shown to produce samples at least 7% better than those generated by the corresponding parallel method, with 99% confidence. Further results are discussed and conclusions are presented.