Rostering with a Hybrid Genetic Algorithm
Human workforce is an expensive resource and therefore should be used as efficient as possible. This optimization task is quite difficult especially in situations where staff members are different in their skills, qualifications or the details of their employment contracts, i.e. these constraints make the optimization of rosters achallenging and difficult task. In this paper we show how Genetic Algorithms combined with problem specific knowledge can be successfully applied to solve such scheduling and planning problems.
KeywordsGenetic Algorithm Repair Operator Penalty Cost Soft Constraint Late Shift
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