A harmony search algorithm for nurse rostering problems

Hadwan, Mohammed; Ayob, Masri; Sabar, Nasser R.; Qu, Rong

doi:10.1016/j.ins.2012.12.025

Cited by 78 publications

(56 citation statements)

References 46 publications

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“…Their study did not investigate how HS would perform for large or complex NRP instances. To overcome this limitation, Hadwan et al [28] used a real dataset from a large hospital in Malaysia to assess the performance of HS and evaluated nurse rostering benchmark problems using their advanced nurse rostering model (ANROM) [30].…”

Section: Introductionmentioning

confidence: 99%

Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem

et al. 2017

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Abstract:The nurse rostering problem is an important search problem that features many constraints. In a nurse rostering problem, these constraints are defined by processes such as maintaining work regulations, assigning nurse shifts, and considering nurse preferences. A number of approaches to address these constraints, such as penalty function methods, have been investigated in the literature. We propose two types of hybrid metaheuristic approaches for solving the nurse rostering problem, which are based on combining harmony search techniques and artificial immune systems to balance local and global searches and prevent slow convergence speeds and prematurity. The proposed algorithms are evaluated against a benchmarking dataset of nurse rostering problems; the results show that they identify better or best known solutions compared to those identified in other studies for most instances. The results also show that the combination of harmony search and artificial immune systems is better suited than using single metaheuristic or other hybridization methods for finding upper-bound solutions for nurse rostering problems and discrete optimization problems.

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Section: Introductionmentioning

confidence: 99%

Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem

et al. 2017

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“…The method is inspired from the underlying principles of the musicians improvisation of the harmony. During the recent years, it has been successfully applied to different optimization problems such as structural design [15], feature selection [10,27], music composition [16], nurse roistering [18], Sudoku puzzle [14], manufacturing optimization problems [46], medical physics [37] and image segmentation [1]. Other applications of HS algorithm (HSA) can be found in [4,36,45] due to its simplicity, generality and flexibility and its lower parameter sensitivity [4], etc.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Harmony Search Combined with Stochastic Local Search for Feature Selection

Nekkaa

Boughaci

2015

Neural Process Lett

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Feature selection is a challenging task that has been the subject of a large amount of research, especially in relation to classification tasks. It permits to eliminate the redundant attributes and enhance the classification accuracy by keeping only the relevant attributes. In this paper, we propose a hybrid search method based on both harmony search algorithm (HSA) and stochastic local search (SLS) for feature selection in data classification. A novel probabilistic selection strategy is used in HSA-SLS to select the appropriate solutions to undergo stochastic local refinement, keeping a good compromise between exploration and exploitation. In addition, the HSA-SLS is combined with a support vector machine (SVM) classifier with optimized parameters. The proposed HSA-SLS method tries to find a subset of features that maximizes the classification accuracy rate of SVM. Experimental results show good performance in favor of our proposed method.

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“…For example, Hadwan et al [4] investigated how to minimize the penalty cost of a nurse schedule. Aickelin and Dowsland [1] applied a genetic algorithm to solve the nurse shift schedule problem in hospitals with the aim to minimize the penalty cost for not fulfilling the preferences of the nursing staff.…”

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confidence: 99%

A Mathematical Model for Nurse Scheduling with Different Preference Ranks

Lin

Kang

Liu³

2015

Lecture Notes in Electrical Engineering

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On nurse shift schedules, it is common that the nursing staff have diverse preferences about shift rotations and days off. We propose a nurse scheduling model based upon integer programming under the constraints of the schedule, different preference ranks towards each shift and the historical data of previous schedule periods so that the nursing staff's preference satisfaction about the shift schedule is maximized. The main difference of the proposed model from the previous works is to consider that the nursing staff's satisfaction level is affected by preference ranks and their priority ordering to be scheduled, so that the quality of shift schedule is more reasonable.

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A harmony search algorithm for nurse rostering problems

Cited by 78 publications

References 46 publications

Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem

Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem

Hybrid Harmony Search Combined with Stochastic Local Search for Feature Selection

A Mathematical Model for Nurse Scheduling with Different Preference Ranks

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