Scheduling resource-constrained projects with a flexible project structure Diskussionsbeitrag AbstractIn projects with a flexible project structure, the activities that have to be scheduled are not completely known beforehand. Instead, scheduling such a project includes the decision whether to carry out particular activities at all. This also effects precedence constraints between the finally implemented activities. However, established model formulations and solution approaches for the resource-constrained project scheduling problem (RCPSP) assume that the project structure is given in advance. In this paper, the traditional RCPSP is hence extended by a highly general model-endogenous decision on this flexible project structure. This is illustrated by the example of the aircraft turnaround process at airports. We present a genetic algorithm to solve this type of scheduling problem and evaluate it in an extensive numerical study.

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We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity constraints can often be systematically modified by temporarily assigning costly additional production resources or using overtime. We, furthermore, assume that the revenue of the project decreases as its makespan increases and try to find a schedule with a profitmaximizing makespan. Like the RCPSP, the problem is NP-hard, but unlike the RCPSP, it turns out that an optimal schedule does not have to be among the set of so-called active schedules. Scheduling such a project is a formidable task, both from a practical and a theoretical perspective. We develop, describe, and evaluate alternative solution encodings and schedule decoding mechanisms to solve this problem within a genetic algorithm framework and we compare the solutions obtained to both optimal reference values and the results of a commercial local search solver called LocalSolver.