Over the last fewyears, the efficient design of processes in hospitals and medical facilities
has received more and more attention, particularly when the improvement of the processes
is aimed at relieving theworkload of medical staff. To this end,we have developed a method
to determine optimal allocations of intra-hospital transports to hospital transport employees.
When optimizing transport plans in hospitals, there are various optimization goals to
strive for. Therefore, we used a lexicographic approach to solve this multi-criteria optimization
problem. In order to calculate optimal transport plans in a sufficiently short computation
time, we have decomposed the problem at hand with the Dantzig-Wolfe reformulation
and solved the resulting pricing subproblem with an enumerative column generation
approach based on Krumke et al. [23]. For improving the efficiency of the column generation
process,we have investigated and implemented different pruning methods, dominance
rules and a column reuse mechanism for the online setting of the application at hand. In
an extensive computational study, we first evaluated the efficiency of the different pruning
methods before we compared our solution approach with the standard branch-and-bound
column search approach from Bärmann et al. [5], classical column generation methods and
the solution of an integrated MIP model solved by a commercial solver. Finally, we present
performance indicators of the transport optimization tool, which was developed from our
method and is now productively used in a German hospital.