Staff Scheduling with Particle Swarm Optimisation and Evolution Strategies

Authors:
Volker Nissen;Maik Günther
Affiliations:
Chair of Information Systems in Services, Technical University of Ilmenau, Ilmenau, Germany D-98684;Chair of Information Systems in Services, Technical University of Ilmenau, Ilmenau, Germany D-98684
Venue:
EvoCOP '09 Proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization
Year:
2009

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Abstract

The current paper uses a scenario from logistics to show that modern heuristics, and in particular particle swarm optimization (PSO) can significantly add to the improvement of staff scheduling in practice. Rapid, sub-daily planning, which is the focus of our research offers considerable productivity reserves for companies but also creates complex challenges for the planning software.