Climbing Harmony Search Algorithm for Nurse Rostering Problems

Hadwan, Mohammed; Ayob, Masri; Al-Hagery, Mohammed Abdullah; Al-Tamimi, Bassam Naji

doi:10.1007/978-3-319-99007-1_8

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…Since NSP is an NP-hard problem, 25 several heuristic and meta-heuristic approaches have been introduced over the past two decades to reach near-optimal solutions in a reasonable time. Some of these approaches include tabu search (TS), [26][27][28] rolling horizon, 29 harmony search algorithm, 30,31 genetic algorithm, [32][33][34][35] spreadsheet-based two-phase heuristic algorithm, 36 simulated annealing, 37,38 two-stage swapping heuristic coupled with a column generation, 39 hybridization of harmony search algorithm and a hill-climbing optimizer, 40 a hybridization of variable neighborhood search accelerated column generation method and a relax-and-fix heuristic, 41 and a hybrid elitist-ant metaheuristic method. 42,43 Nurses' preferences for shifts, and considering their skills in NSPs, have been explored in several studies, which were mentioned above.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Hamid

Tavakkoli–Moghaddam

Golpaygani

et al. 2019

Proc Inst Mech Eng H

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Assigning nurses to appropriate departments and work shifts based on human factors can strengthen teamwork and boost the efficiency of healthcare systems. The human factors considered in this study include skill, preference, and compatibility of nurses. In this regard, a unique multi-objective mathematical model for nurse scheduling is proposed in this article, in which nurses’ decision-making styles are taken into account. Three objectives, including minimization of the total cost of staffing, minimization of the sum of incompatibility among nurses’ decision-making styles assigned to the same shift days, and maximization of the overall satisfaction of nurses for their assigned shifts, are addressed in this model. Three meta-heuristics, namely, multi-objective Keshtel algorithm, non-dominated sorting genetic algorithm II, and multi-objective tabu search, are developed to solve the problem. Moreover, a data envelopment analysis method is employed to rank the obtained Pareto solutions. Afterwards, a real-life case at a large hospital in Tehran, Iran, is investigated. Eventually, the applicability and effectiveness of the proposed model are assessed based on the experimental results.

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Section: Literature Reviewmentioning

confidence: 99%

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Hamid

Tavakkoli–Moghaddam

Golpaygani

et al. 2019

Proc Inst Mech Eng H

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“…For medium instances (NICU, N50, ED) and large instances (SGY and CICU), AHSA generates very high-quality rosters with very low PVs. To further evaluate the performance of the AHSA, it was compared to previously published work of other HSA hybridized algorithms the CHSA [6] and DHSA [8]). The results in Tab.…”

Section: Comparison Between the Chsa Dhsa Ehsa Has And Ahsamentioning

confidence: 99%

“…Several attempts have been made in the literature to hybridize the original and enhanced HSA with other local search algorithms to improve its performance [5]. The HSA has been hybridized with other heuristic-based algorithms, such as hillclimbing [6,7], great deluge [8], simulated annealing [9,10], and particle swarm optimization [11]. For the process of diversification and intensification, the hybridization of population-based methods with local search-based methods has been considered by many researchers to strike the balance between these processes [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…AHSA then used to solve a real-world NRP belonging to the medical centre of National University Malaysia (UKMMC). To show the strength of the introduced algorithm, the AHSA is evaluated and compared against previous variants of the HSA in [6,8,16] in addition to another algorithm from the literature that hybridizes the HSA with the SA and is called the HAS [9]. This research is an extension of previous works aimed at improving the EHSA [16] by hybridizing it with other local-search algorithms, such as the hill-climbing [6] and great deluge [8] algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…To show the strength of the introduced algorithm, the AHSA is evaluated and compared against previous variants of the HSA in [6,8,16] in addition to another algorithm from the literature that hybridizes the HSA with the SA and is called the HAS [9]. This research is an extension of previous works aimed at improving the EHSA [16] by hybridizing it with other local-search algorithms, such as the hill-climbing [6] and great deluge [8] algorithms. These algorithms were selected because of their diverse acceptance criteria and the different mechanisms to the use to avoid being trapped in local optima.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Annealing Harmony Search Algorithm to Solve the Nurse Rostering Problem

Hadwan¹

2022

Computers, Materials &Amp; Continua

Self Cite

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A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in general have problems striking the balance between diversification and intensification. Therefore, this paper aims to introduce a novel metaheuristic hybridization that combines the enhanced harmony search algorithm (EHSA) with the simulated annealing (SA) algorithm called the annealing harmony search algorithm (AHSA). The AHSA is used to solve NRP from a Malaysian hospital. The AHSA performance is compared to the EHSA, climbing harmony search algorithm (CHSA), deluge harmony search algorithm (DHSA), and harmony annealing search algorithm (HAS). The results show that the AHSA performs better than the other compared algorithms for all the tested instances where the best ever results reported for the UKMMC dataset.

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Healthcare scheduling in optimization context: a review

et al. 2021

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This paper offers a summary of the latest studies on healthcare scheduling problems including patients’ admission scheduling problem, nurse scheduling problem, operation room scheduling problem, surgery scheduling problem and other healthcare scheduling problems. The paper provides a comprehensive survey on healthcare scheduling focuses on the recent literature. The development of healthcare scheduling research plays a critical role in optimizing costs and improving the patient flow, providing prompt administration of treatment, and the optimal use of the resources provided and accessible in the hospitals. In the last decades, the healthcare scheduling methods that aim to automate the search for optimal resource management in hospitals by using metaheuristics methods have proliferated. However, the reported results are disintegrated since they solved every specific problem independently, given that there are many versions of problem definition and various data sets available for each of these problems. Therefore, this paper integrates the existing results by performing a comprehensive review and analyzing 190 articles based on four essential components in solving optimization problems: problem definition, formulations, data sets, and methods. This paper summarizes the latest healthcare scheduling problems focusing on patients’ admission scheduling problems, nurse scheduling problems, and operation room scheduling problems considering these are the most common issues found in the literature. Furthermore, this review aims to help researchers to highlight some development from the most recent papers and grasp the new trends for future directions.

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Climbing Harmony Search Algorithm for Nurse Rostering Problems

Cited by 5 publications

References 17 publications

A multi-objective model for a nurse scheduling problem by emphasizing human factors

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Annealing Harmony Search Algorithm to Solve the Nurse Rostering Problem

Healthcare scheduling in optimization context: a review

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