Insightful modelling and algorithm development for nurse rostering

Katholieke Universiteit Leuven


October 22, 2022


Insightful modelling and algorithm development for nurse rostering

(ref. BAP-2022-710)

Last modification : Wednesday, September 21, 2022

The general research theme of CODeS concerns the design, analysis and application of heuristics for a wide range of combinatorial optimisation problems. CODeS members have constructed models and investigated the behaviour and application of metaheuristics at the forefront of combinatorial optimisation research for over twenty years. Examples of such approaches include mathematical programming, heuristics, local search-based metaheuristics. CODeS pursues both generic models and dedicated, custom-fit algorithmic approaches for a wide range of application domains which include real-world scheduling, timetabling, logistics, transportation, cutting and packing. Given its historical and continued involvement in various industrial projects and its participation in Leuven.AI and Leuven Institute for Mobility, CODeS constitutes a highly-qualified research group with a successful track record with regard to synergy and valorisation of its academic expertise, thereby positioning itself at the cutting edge of emerging system design and development methodologies. CODeS actively seeks interdisciplinary research opportunities through which it may further strengthen and innovate its modeling and development expertise by applying the latest discoveries within its domain across a broad range of applications. This joint PhD will be partly conducted at the University of Melbourne (https: //, supervised by Prof Kate Smith-Miles and Prof Alysson Costa.

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Efficient algorithms for complex personnel scheduling problems are critical for ensuring organisations can provide a

suitably qualified workforce at minimal cost while satisfying a wide variety of strict regulations meeting

occupational health and safety requirements, as well as employee preferences. This PhD project will focus on nurse

rostering, where nurses must be optimally allocated to work shifts in a manner that ensures their specialised

expertise is available when required to support scheduled surgeries and other activities, while satisfying rules about

shift lengths, leave days, and accommodating as much as possible their individual preferences.

The University of Melbourne has strong expertise in tackling related scheduling problems, but will benefit

enormously from the specific expertise of the KU Leuven team developed over several decades in advancing

models and algorithms for the nurse rostering problem. The partnership will enable new collaborative links with

Melbourne based hospitals to be forged to support this PhD project, via the new ARC Training Centre in

Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA), in which the PhD student will be

based. The KU Leuven team will also benefit from application of the University of Melbourne's Instance Space

Analysis methodology to gain deep insights into the strengths and weaknesses of nurse rostering algorithms, and

ensure that the project's newly developed algorithmic advances are rigorously “stress tested” to understand their

robustness and reliability for a wide range of hospital settings in both Australia and Belgium.


We are looking for a graduate (MSc or equivalent) in mathematics, operations research, computer science or engineering. Modelling experience and good programming skills are essential.


The successful candidate will be offered a full PhD grant. The home institution will be KU Leuven whilst a substantial research period will be spent at the University of Melbourne.

The proposed PhD project thus offers an outstanding opportunity for the student to be supported by the

complementary expertise of two world class groups, keen to formally work together for the mutual benefit of their

individual research agendas, and for the benefit of industry partners in both Australia and Belgium. Two students will be working together,

each on a different industrial optimisation problem – but with a similar macro-scale roadmap:

developing models, designing algorithms, stress-testing using instance space analysis, taking insights to propose

new algorithms, and validating on industry case studies.


For more information please contact Prof. dr. ir. Greet Vanden Berghe, tel.: +32 9 265 87 03, mail: or Mr. Pieter Smet, mail:

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at

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Insightful modelling and algorithm development for nurse rostering

Insightful modelling and algorithm development for nurse rostering The general research theme of CODeS concerns the design, analysis and application of heuristics for a wide range of combinatorial optimisation algorithmic approaches for a wide range...