Simple Genetic Algorithm (SGA) as feature selector, route optimization for home care service with SGA and semantic segmentation using Multiobjective Genetic Algorithm (MOGA)
Initialization takes forever, so must introduce a construction heuristic for the initial population.
Thinking of using KNN with the data points to generate clusters of patients.
[ ] Assign n patients to clusters dependent on
Calculate cluster demand
Check for patient overlap (number of concurrent overlaps).
Optimistic approach
Check the time windows and try to arrange the patients accordingly. Do we need the same amount of nurses as overlaps, or could we fit in the patients such that less nurses can attend to them?
[ ] Calculate cluster's start- and endtime so nurses of other clusters can be assigned if necessary.
Constraints
Check for constraints within a cluster
If cluster is not ok, halt and wait for other clusters to finish. Then try to assign an available nurse from another cluster
Initialization takes forever, so must introduce a construction heuristic for the initial population.
Thinking of using KNN with the data points to generate clusters of patients.
Constraints
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