Neue Publikation in OR Perspectives
Wir freuen uns über eine neue hochrangige Veröffentlichung unter Mitwirkung von Janis Neufeld in der Zeitschrift Operation Research Perspectives! In einigen Fertigungsprozessen, wie zum Beispiel in Gewächshäusern, können mehrere Arbeitsaufträge gleichzeitig ausgeführt werden. In unserem Beitrag stellen wir einen neuen Ansatz zur Maschinenbelegungsplanung vor und zeigen, wie eine intelligentere Planung die Effizienz steigern und Wartezeiten verkürzen kann.
Beitrag
Ahmed Missaoui, Janis S. Neufeld, Barry O’Sullivan Local search methods for the cumulative flow shop scheduling problem, Operations Research Perspectives 17 (2026)
https://doi.org/10.1016/j.orp.2026.100403
Abstract
Scheduling problems are typically studied under the assumption that each resource can process only one job at a time. However, in many real-world settings, resources are capable of processing multiple jobs simultaneously, leading to cumulative scheduling problems, where each resource can process several jobs up to a specified capacity. While cumulative scheduling has been investigated in job shops and parallel-machine contexts, it remains unexplored in flow shop environments. In this work, we introduce the cumulative flow shop scheduling problem as a generalization of the classical flow shop. We propose a mixed-integer programming formulation along with two metaheuristic approaches – an iterated local search algorithm and an iterated greedy algorithm – designed to minimize total flow time. Both methods incorporate problem-specific features, such as an adapted initial solution and a rescheduling mechanism to improve resource utilization. With this, they demonstrate strong performance in a comprehensive computational study. Additionally, we analyze trade-offs between total flow time and resource utilization, and investigate how varying job sizes and resource capacities affect outcomes. Our findings provide actionable managerial insights and open new avenues for research on cumulative scheduling problems.
