Good afternoon.
I have developed an application to efficiently schedule chemotherapy
patients at our hospital. The application takes into account several
resource constraints (available chairs, available nurses, nurse coverage
assignment to chairs) as well as the chair time and nursing time
required for a regimen.
The algorithm for packing appointments in respects each constraint and
typically schedules a day of treatments (30-60) within 9-10 seconds on
my workstation, down from 27 seconds initially. I would like to get it
below 5 seconds if possible.
I think what's slowing is down is simply the number of rows and joins.
The algorithm creates a scheduling matrix with one row per 5 minute
timeslot, per unit, per nurse assigned to the unit. That translates to
3,280 rows for the days I have designed in development (each day can
change).
To determine the available slots, the algorithm finds the earliest slot
that has an available chair and a count of the required concurrent
intervals afterwards. So a 60 minute regimen requires 12 concurrent
rows. This is accomplished by joining the table on itself. A second
query is ran for the same range, but with respect to the nurse time and
an available nurse. Finally, those two are joined against each other.
Effectively, it is:
Select *
From (
Select *
From matrix m1, matrix m2
Where m1.xxxxx = m2.xxxxx
) chair,
(
Select *
From matrix m1, matrix m2
Where m1.xxxxx = m2.xxxxx
) nurse
Where chair.id = nurse.id
With matrix having 3,280 rows. Ugh.
I have tried various indexes and clustering approachs with little
success. Any ideas?
Thanks,
Matthew Hartman
Programmer/Analyst
Information Management, ICP
Kingston General Hospital
(613) 549-6666 x4294
