The purpose of this paper is to develop two ef® cient 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.
The main purposes of this study are to incorporate both the project delay penalty and early completion bonus into the objective function of the resource-constrained multi-project scheduling problem with discounted cash flows (RCMPSP-DCF) and to develop an efficient heuristic search scheduling rule. The effectiveness of the proposed heuristic rule is evaluated by comparing it with the optimal solution obtained by the optimal model for 42 small-scale problems. The result indicates that the solution obtained using the proposed heuristic rule is very close to the optimal solution, and that the proposed heuristic rule provides significant savings in computation time. Moreover, the proposed heuristic rule is also compared with four existing heuristic rules based on an experiment involving the single-project and multi-project scheduling problems. The results indicate that the proposed heuristic rule is superior to the four existing rules under the performance criteria of the average total project net present value and the average total project delay. In addition, the number of times that the proposed heuristic rule can obtain the best solution is also far more than that of any other rule considered in this paper under the two aforementioned performance criteria. Furthermore, this study has found that the performance of a heuristic scheduling rule is significantly affected by the number of projects. A rule that can lower the total project delay to the minimum is also able to maxi5 mize the total project net present value.Multi-PROJECT Scheduling, Project Management, Resource Constraints, Net Present Value, Heuristic Rules,
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