Home Care optimization: impact of pattern generation policies on scheduling and routing decisions

Abstract In Home Care optimization, operators have to be assigned to patients by taking into account compatibility skill constraints, and patient visits have to be scheduled in a given planning horizon. Moreover, operator tours have to be determined. Integer Linear Programming models have been proposed which use the concept of patterns, i.e. a priori scheduling profiles, to combine the diverse decision levels. Computational results on real instances show that pattern generation policies are crucial to address scheduling and routing in large Home Care instances.