Hospital bed planning (PAS - Patient Admission Scheduling)
Problem description
Assign each patient (that will come to the hospital) into a bed for each night that the patient will stay in the hospital. Each bed belongs to a room and each room belongs to a department. The arrival and departure dates of the patients is fixed: only a bed needs to be assigned for each night.
This problem features overconstrained datasets.
Hard constraints:
-
Two patients must not be assigned to the same bed in the same night. Weight:
-1000hard * conflictNightCount. -
A room can have a gender limitation: only females, only males, the same gender in the same night or no gender limitation at all. Weight:
-50hard * nightCount. -
A department can have a minimum or maximum age. Weight:
-100hard * nightCount. -
A patient can require a room with specific equipment(s). Weight:
-50hard * nightCount.
Medium constraints:
-
Assign every patient to a bed, unless the dataset is overconstrained. Weight:
-1medium * nightCount.
Soft constraints:
-
A patient can prefer a maximum room size, for example if he/she wants a single room. Weight:
-8soft * nightCount. -
A patient is best assigned to a department that specializes in his/her problem. Weight:
-10soft * nightCount. -
A patient is best assigned to a room that specializes in his/her problem. Weight:
-20soft * nightCount.-
That room speciality should be priority 1. Weight:
-10soft * (priority - 1) * nightCount.
-
-
A patient can prefer a room with specific equipment(s). Weight:
-20soft * nightCount.
The problem is a variant on Kaho’s Patient Scheduling and the datasets come from real world hospitals.
Problem size
overconstrained01 has 6 specialisms, 4 equipments, 1 departments, 25 rooms, 69 beds, 14 nights, 519 patients and 519 admissions with a search space of 10^958.
testdata01 has 4 specialisms, 2 equipments, 4 departments, 98 rooms, 286 beds, 14 nights, 652 patients and 652 admissions with a search space of 10^1603.
testdata02 has 6 specialisms, 2 equipments, 6 departments, 151 rooms, 465 beds, 14 nights, 755 patients and 755 admissions with a search space of 10^2015.
testdata03 has 5 specialisms, 2 equipments, 5 departments, 131 rooms, 395 beds, 14 nights, 708 patients and 708 admissions with a search space of 10^1840.
testdata04 has 6 specialisms, 2 equipments, 6 departments, 155 rooms, 471 beds, 14 nights, 746 patients and 746 admissions with a search space of 10^1995.
testdata05 has 4 specialisms, 2 equipments, 4 departments, 102 rooms, 325 beds, 14 nights, 587 patients and 587 admissions with a search space of 10^1476.
testdata06 has 4 specialisms, 2 equipments, 4 departments, 104 rooms, 313 beds, 14 nights, 685 patients and 685 admissions with a search space of 10^1711.
testdata07 has 6 specialisms, 4 equipments, 6 departments, 162 rooms, 472 beds, 14 nights, 519 patients and 519 admissions with a search space of 10^1389.
testdata08 has 6 specialisms, 4 equipments, 6 departments, 148 rooms, 441 beds, 21 nights, 895 patients and 895 admissions with a search space of 10^2368.
testdata09 has 4 specialisms, 4 equipments, 4 departments, 105 rooms, 310 beds, 28 nights, 1400 patients and 1400 admissions with a search space of 10^3490.
testdata10 has 4 specialisms, 4 equipments, 4 departments, 104 rooms, 308 beds, 56 nights, 1575 patients and 1575 admissions with a search space of 10^3922.
testdata11 has 4 specialisms, 4 equipments, 4 departments, 107 rooms, 318 beds, 91 nights, 2514 patients and 2514 admissions with a search space of 10^6295.
testdata12 has 4 specialisms, 4 equipments, 4 departments, 105 rooms, 310 beds, 84 nights, 2750 patients and 2750 admissions with a search space of 10^6856.
testdata13 has 5 specialisms, 4 equipments, 5 departments, 125 rooms, 368 beds, 28 nights, 907 patients and 1109 admissions with a search space of 10^2847.