The well-known deterministic resource-constrained project scheduling problem involves the determination of a predictive schedule (baseline schedule or pre-schedule) of the project activities that satisfies the finish-start precedence relations and the renewable resource constraints under the objective of minimizing the project duration. This baseline schedule serves as a baseline for the execution of the project. During execution, however, the project can be subject to several types of disruptions that may disturb the baseline schedule. Management must then rely on a reactive scheduling procedure for revising or reoptimizing the baseline schedule. The objective of our research is to develop procedures for allocating resources to the activities of a given baseline schedule in order to maximize its stability in the presence of activity duration variability. We propose three integer programming-based heuristics and one constructive procedure for resource allocation. We derive lower bounds for schedule stability and report on computational results obtained on a set of benchmark problems.

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The well-known deterministic resource-constrained project scheduling problem (RCPSP) involves the determination of a predictive schedule (baseline schedule or pre-schedule) of the project activities that satisfies the finish-start precedence relations and the renewable resource constraints under the objective of minimizing the project duration. This pre-schedule serves as a baseline for the execution of the project. During execution, however, the project can be subject to several types of disruptions that may disturb the baseline schedule. Management must then rely on a reactive scheduling procedure for revising or reoptimizing the pre-schedule.The objective of our research is to develop procedures for allocating resources to the activities of a given baseline schedule in order to maximize its stability in the presence of activity duration variability. We propose three integer programming based heuristics and one constructive procedure for resource allocation. We derive lower bounds for schedule stability and report on computational results obtained on a set of benchmark problems.

In this article we discuss a freely downloadable educational software tool for illustrating project scheduling and project management concepts. The tool features exact and heuristic scheduling procedures and visualizes project networks, project schedules, resource profiles, activity slacks, and project duration distributions. ß