Extending the RCPSP for modeling and solving disruption management problems

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 31; no. 3; pp. 234 - 253
• Main Authors: Kuster, Jürgen, Jannach, Dietmar, Friedrich, Gerhard
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.12.2009; Springer Nature B.V
• Subjects: Aircraft; Algorithms; Artificial Intelligence; Computer Science; Disruption; Focusing; Intelligence; Machines; Management; Manufacturing; Mathematical models; Mechanical Engineering; Optimization; Processes; Studies; Scheduling; Disruption management; Applications; Genetic algorithms
• ISSN: 0924-669X; 1573-7497
• DOI: 10.1007/s10489-008-0119-x

This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem for the comprehensive description of disruption management problems. This conceptual framework employs the concept of alternative activities to consider both the temporal shift of activities or the reallocation of resources and switches from one valid process variant to another one. Activities can be serialized or parallelized, process steps can be inserted or removed and durations as well as resource requirements can be modified dynamically during optimization. Focusing on the domain of the aircraft turnaround as the most important airport ground process, we illustrate how the Extended RCPSP ( x-RCPSP ) can be applied for decision support. A specific evolutionary algorithm is presented that identifies good-quality solutions to relatively large disruption management problems within only a few seconds. The results of the evaluation illustrate fast convergence on good or optimal schedules and serve as a basis for the development of future problem solving algorithms.