Cooperative search for fair nurse rosters

Abstract

The development of decision support systems acceptable for nurse rostering practitioners still presents a daunting challenge. Building on an existing nurse rostering problem, a set of fairness-based objective functions recently introduced in the literature has been extended. To this end, a generic agentbased cooperative search framework utilising new mechanisms is described, aiming to combine the strengths of multiple metaheuristics. These different metaheuristics represent individual planners' implicit procedures for improving rosters. The framework enables to explore different ways of assessing nurse rosters in terms of fairness objectives. Computational experiments have been conducted across a set of benchmark instances. The overall results indicate that the proposed cooperative search for fair nurse rosters outperforms each metaheuristic run individually.

Nurse rostering: models and algorithms for theory, practice and integration with other problems

“…Despite possible differences between countries, the core problem remains the same: assign a shift or day-off to each nurse on each day of the scheduling period, taking into account a set of personal, organisational and legislative constraints. The academic literature offers many different solution techniques to this problem, ranging from exact methods [55,85] over metaheuristics [82,90] to hybrid approaches [40,118]. Although the problem has received considerable attention in the last decades, several important open issues remain in the academic literature.…”

Inequity averse optimization in operational research

“…One of the popular problems in scheduling where equity plays a crucial role arises in healthcare organizations where nurses' or physicians' schedules are constructed (Azaiez & Al Sharif, 2005;Stolletz & Brunner, 2012;Tsai & Li, 2009;Martin et al, 2013). In such settings providing an equitable distribution of workload across the nurses or physicians is important.…”

“…It is possible to use the total absolute deviations from the mean ( i∈I |y i − y|, where y = i∈I y i m |) (Ogryczak, 2009;Eiselt & Marianov, 2008;Martin et al, 2013;Bergey et al, 2003;Bertsimas et al, 2014;López-de-los Mozos et al, 2013) or to use the positive or negative deviations only, as in Ogryczak (2009). The mean deviation does not satisfy strong PD because it is not affected by transfers between two entities which are both above the mean or both below it.…”

“…They discuss the models for cyclic, tree and path networks. Martin et al (2013) minimize a convex function of the form i∈I y 2 i to ensure that violations of soft constraints in nurses' rosters are equitably distributed across nurses in a scheduling problem. Similarly, Kunqi et al (2007) maximize an additive concave utility function of the form U = i∈I −W h i / h for h ≥ 1, where W i deotes the waiting time user i in a wireless network and h is a parameter.…”

A multi-agent based optimization method applied to the quadratic assignment problem

“…Our work is motivated by appealing features of a MAS which could be advantageously used to elaborate intelligent computing systems (Martin, Ouelhadj, Smetb, Beullens, &Özcan, 2013;Guo, Goncalves, & Hsu, 2013;Gonçalves, Guimarães, & Souza, 2014;Satunin & Babkin, 2014;Couellan, Jan, Jorquera, & Georgé, 2015;Baykasoglu & Kaplanoglu, 2015;Zheng & Wang, 2015). Compared with the existing studies on the QAP, this work has the following main contributions:…”