David Sier

Staff scheduling and rostering: A review of applications, methods and models

Abstract This paper presents a review of staff scheduling and rostering, an area that has become increasingly important as business becomes more service oriented and cost conscious in a global environment. Optimised staff schedules can provide enormous benefits, but require carefully implemented decision support systems if an organisation is to meet customer demands in a cost effective manner while satisfying requirements such as flexible workplace agreements, shift equity, staff preferences, and part-time work. In addition, each industry sector has its own set of issues and must be viewed in its own right. There are many computer software packages for staff scheduling, ranging from spreadsheet implementations of manual processes through to mathematical models using efficient optimal or heuristic algorithms. We do not review software packages in this paper. Rather, we review rostering problems in specific application areas, and the models and algorithms that have been reported in the literature for their solution. We also survey commonly used methods for solving rostering problems.

An Annotated Bibliography of Personnel Scheduling and Rostering

Computational methods for rostering and personnel scheduling has been a subject of continued research and commercial interest since the 1950s. This annotated bibliography puts together a comprehensive collection of some 700 references in this area, focusing mainly on algorithms for generating rosters and personnel schedules but also covering related areas such as workforce planning and estimating staffing requirements. We classify these papers according to the type of problem addressed, the application areas covered and the methods used. In addition, a short summary is provided for each paper.

Staff rostering at a large international airport

The human resource planning and scheduling system described in this paper assists in the rostering of approximately 500 staff for the airport operations of a major international airline at one of the busiest international airports. The system rosters airline ground staff over a monthly planning horizon so that the work load is evenly distributed among the staff and idle time, the main productivity measure, is minimised. The rosters are subject to a large number of rules designed to ensure reasonable working conditions and service stand-ards. The system then allocates individual tasks to the staff for any particular day, and effectively manages, in real-time, disruptions that occur due to aircraft delays and unplanned staff absences on the day of operations. The system is also designed to reduce the number of staff needed to run the present rostering system. In this paper, we provide a description of the overall system and an algorithm for solving the rostering problem associated with the system.

An Integrated Optimization Model for Train Crew Management

Train crew management involves the development of a duty timetable for each of the drivers (crew) to cover a given train timetable in a rail transport organization. This duty timetable is spread over a certain period, known as the roster planning horizon. Train crew management may arise either from the planning stage, when the total number of crew and crew distributions are to be determined, or from the operating stage when the number of crew at each depot is known as input data. In this paper, we are interested in train crew management in the planning stage. In the literature, train crew management is decomposed into two stages: crew scheduling and crew rostering which are solved sequentially. We propose an integrated optimization model to solve both crew scheduling and crew rostering. The model enables us to generate either cyclic rosters or non-cyclic rosters. Numerical experiments are carried out over data sets arising from a practical application.

A mixed integer programming model for long term capacity expansion planning: A case study from The Hunter Valley Coal Chain

The Hunter Valley Coal Chain is the largest coal export operation in the world with a throughput in excess of 100 million tonnes per annum (Mtpa). Coal is delivered to the shipping terminal from 40 mines using 27 coal load points spread across the Hunter Valley region. This paper describes an MILP model for determining the capacity requirements, and the most cost effective capacity improvement initiatives, to meet demand while minimising the total cost of infrastructure and demurrage. We present results from computational experiments on the model’s performance along with a comparison of the model’s output with detailed analyses by the coal chain analysts and planners.

An automated itinerary planning system for holiday travel

This article describes a prototype travel recommender system called the Electronic Travel Planner (ETP), which prepares travel itineraries for tourists. The system is driven by models of a traveler’s preferences and requirements, and makes reference to databases containing information pertaining to tourism and travel products. Its main tasks are to select destinations for the traveler to visit, to decide which tours or attractions are to be taken, and to compose a detailed itinerary linking up the chosen components. These tasks entail difficult optimization problems, which the prototype addresses by means of an heuristic problem-solving framework. Computational tests confirm the effectiveness of the methods used, and suggest that an automated approach will be feasible in full-scale travel planning applications.

Discharge timeliness and its impact on hospital crowding and emergency department flow performance.

The objective of this research is to identify optimal inpatient discharge time targets to help hospitals reduce crowding, improve patient flow through the ED and balance staff workload.

Rail Crew Scheduling and Rostering Optimization Algorithms

Train crew rostering involves the development of a duty timetable for each of the drivers of a rail transport organization. This duty timetable is spread over a period known as the roster planning horizon. We propose an optimization approach for an instance of a train crew rostering problem arising from a practical application. The problem involves developing continuous and cyclic work lines (or rosters) for train drivers spread over several depots in a rail network. The rail timetable includes over 1300 trips a week. The rosters for all the crew must conform to complex industrial regulations and work rules. The main objective in this model is to minimize the overall roster cost accrued from using the available crew while providing the requisite number of crew for each train trip in the schedule. The rosters must also satisfy quality standards for all drivers, by attempting to satisfy their personal preferences. We describe the problem and provide optimization formulations and solution approaches. We also present some computational results.

Rail schedule optimisation in the Hunter Valley Coal Chain

This paper describes a method for scheduling trains on the Hunter Valley Coal Chain rail network. Coal for a particular ship is railed from different mines to stockpiles at one of the Port’s terminals. The coal producers decide which mines will supply each order in what proportion, so there is no flexibility in the allocation of mines to cargoes. We are presented with a list of tonnes of coal which need to be transported from specified load points at mines to specified stockpiles at the port. The operators of the rail network provide a number of paths, with specified arrival and departure times, that can be used for coal movement. The requirement to assign coal trains to these existing paths makes this rail scheduling problem different to most of those discussed in the literature. In this paper we describe the problem in detail, demonstrate that it is very large making it difficult to solve with commercial MILP solvers, and show that our Lagrangian heuristic is able to produce high quality solutions in a reasonable amount of time.

MODELLING THE ACUTE HEALTH SYSTEM: PATIENT FLOW ANALYSIS FOR IMPROVED HEALTH SERVICE DELIVERY

Routine collection of health care information by government agencies provides a wealth of potential for improving the delivery of healthcare through the analysis of patient flow. We describe our work in secondary analysis (i.e. differing from the purpose originally intended) of hospital information datasets comprising episodes of patient care. Our patient flow tools and analyses have application to public health agencies striving to improve the productivity and efficiency of service delivery, where evidence-driven strategies are desired to support improved health outcomes.