Automated Staff Scheduling Software
Tim Curtois
The OR Society Criminal Justice Special Interest Group
27 June 2012
Background




The software was originally developed as part of a PhD
research project on automatic scheduling for healthcare
personnel
The research was published and a demo put online
ASAP was approached by a software company interested in
licensing the technology
The University of Nottingham formed a spin-out company
to license the software engine
Automated staff scheduling
2
The Modelling Approach





During the research we collected data and benchmark instances
from lots of different sources (e.g. industrial collaborators, other
researchers)
Became clear that the problems varied significantly from one
workplace to another not just in terms of problem size (e.g. staff
numbers, planning horizon length, numbers and types of shifts)
but also in the variety of working constraints and rules
Developed a model that would allow end-users to define custom
rules and their priorities
Priorities are specified with weights/costs (number values). A
penalty/cost is incurred when a rule cannot be satisfied
Objective is to minimise the sum of all penalties due to constraint
violations
Automated staff scheduling
3
Example Constraints



Employee working constraints - Min/max hours worked,
min/max consecutive days on or off, shift rotations, night
shifts, weekends, shift requests etc
Cover/demand constraints - Min/max required employees
during shifts/time periods (possibly skill/task based)
Ensuring employees work together (or do not work
together)


Training/supervision, car-sharing, productivity based
constraints
Similar skills, couple with children, or two employees just don't
get on!
Automated staff scheduling
4
Problem Versions
1.
2.
Pre-defined shifts with fixed start and finish times (e.g.
early shift, day shift, late shift, night shift)
Shift start and finish times not pre-defined, additional
constraints e.g.

Earliest/latest shift start and finish times

Min/max shift lengths


Break lengths and times (often depending on shift lengths and
start times)
Tasks assigned during shifts
Automated staff scheduling
5
Methodologies

Exact based (e.g. Branch and Price)
Advantages
 Works very well on smaller instances
 Can provide optimal solutions or information on how close to optimal
the solution is
Disadvantages
 On larger instances can require infeasible amounts of memory and
computation times and so may not always return a solution

Heuristic based (e.g. Metaheuristics)
Advantages
 More robust and always returns a solution regardless of instance size
and computation time
Disadvantages
 Outperformed by exact based methods on smaller instances
 No information on how close to optimal the solution is
Automated staff scheduling
6
Demo

…
(Software available at www.staffrostersolutions.com)
Automated staff scheduling
7