Resource-constrained multi-project scheduling with activity and time flexibility. (December 2020)

• Record Type: Journal Article
• Authors: Hauder, Viktoria A.; Beham, Andreas; Raggl, Sebastian; Parragh, Sophie N.; Affenzeller, Michael
• Is Part Of: Computers & industrial engineering. Volume 150(2020)
• Publication Date: 2020-12
• Subjects: Multi-project scheduling -- Activity and time flexibility -- Constraint programming -- Manufacturing; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106857
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: Project scheduling in manufacturing environments often requires flexibility in terms of the selection and the exact length of alternative production activities. Moreover, the simultaneous scheduling of multiple lots is mandatory in many production planning applications. To meet these requirements, a new resource-constrained project scheduling problem (RCPSP) is introduced where both decisions (activity flexibility and time flexibility) are integrated. Besides the minimization of makespan, two new alternative objectives are presented: maximization of balanced length of selected activities (time balance) and maximization of balanced resource utilization (resource balance). New mixed integer and constraint programming (CP) models are proposed for the developed integrated flexible project scheduling problem. Benchmark instances on an already existing flexible RCPSP and the newly developed problem are solved to optimality. The real-world applicability of the suggested CP models is shown by additionally solving a large industry case. Highlights: A new flexible resource-constrained multi-project scheduling problem is introduced. Two new objective functions are presented, focusing on well-balanced solutions. New mixed integer and constraint programming models are proposed. Optimal solutions are provided for benchmark instances. Real-world applicability is demonstrated by solving an industry case to optimality.