Untangling Resource Conflicts

Mario Vanhoucke ()
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Mario Vanhoucke: University of Ghent, Faculty of Economics and Business

Chapter 3 in Data-Driven Project Management with Python, 2026, pp 29-47 from Springer

Abstract: Abstract This chapter provides an introduction to the challenges and opportunities of project scheduling with limited resources. It begins with Sect. 3.1, where the resource-constrained project scheduling problem (RCPSP) is introduced, the potential presence of resource conflicts in critical path schedules is explained, and three illustrative projects are presented as running examples for the experiments that follow. In Sect. 3.2, the Python-based framework is used to conduct two experiments, giving readers the chance to explore how priority rules, exact methods, and heuristic approaches behave under different project conditions. The third section, Sect. 3.3, briefly summarizes 10 of my published research studies on the RCPSP, offering both an overview of recent trends in the field and, admittedly, a short “commercial break” to promote my latest book. Finally, Sect. 3.4 reflects on the limitations of current approaches by revisiting state-of-the-art algorithms and, more importantly, by looking ahead to the potential role of artificial intelligence in project scheduling. This chapter shows that while the RCPSP is notoriously complex, it also continues to inspire new methods, tools, and ideas. The chapter aims not only to explain the fundamentals but also to spark curiosity, inviting readers to contribute to the ongoing search for better ways to schedule projects with scarce resources.

Keywords: Resources constraints; Time minimisation; Net present value; Scheduling heuristics (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-24556-4_3

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