Two heuristics for scheduling multiple projects with resource constraints

The purpose of this paper is to develop two efficient heuristic priority rules for the resource-constrained multiproject scheduling problem. The aptness of the two heuristic rules is analysed in terms of several dynamic characteristics of the scheduling problem. Fifteen heuristic rules presented in previous studies are used for comparison with the two heuristic rules on 4941 test problems which were generated by combining two, three or four projects from seven typical networks. The results indicate that the two proposed heuristics are superior to the other scheduling rules under the performance criteria of the minimum total project delay and the maximum number of times that a scheduling rule can obtain the best solution. Encouragingly, the two heuristic rules are proven to be adaptive and stable enough for scheduling under different problem sizes, network structures and degrees of resource tightness. As a result, the two proposed rules are the best representatives of the single priority rule method and the weighted combination search method, respectively. This study also includes a categorization process on which a project summary measure is based and then provides project schedulers with a convenient scheme to adopt appropriate scheduling rules.