![]() Creating an optimal schedule for a realistic. A set of new challenging instances is now available to the academic community. constrained multiagent task scheduling problems with scala- bility towards large problem sizes. The empirical hardness results enable to generate hard problem instances. These insights are useful when deciding on organisational policies to better manage various operational aspects related to workforce. The influence of a set of problem instance features on the performance of different algorithms is investigated in order to discover what makes particular problem instances harder than others. Computational results show that the new hybrid method is capable of finding, for the first time, optimal solutions for all benchmark instances from the literature, in very limited computation time. The present paper introduces a new, versatile two-phase matheuristic approach to the shift minimisation personnel task scheduling problem, which considers assigning tasks to a set of multi-skilled employees, whose working times have been determined beforehand. Optimising the use and composition of costly and scarce resources such as staff has major implications on any organisation׳s health. ![]() ![]() Assigning scheduled tasks to a multi-skilled workforce is a known NP-complete problem with many applications in health care, services, logistics and manufacturing.
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