Hybrid Harmony Search for Stochastic Scheduling of Chemotherapy Outpatient Appointments

Corsini, Roberto Rosario; Costa, Antonio; Fichera, Sergio; Parrinello, Vincenzo

doi:10.3390/a15110424

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…They also propose a novel algorithm called scenario bundlingbased decomposition (SBBD) to solve the model and evaluate the effectiveness of their proposed approach. Some of the other studies that develop stochastic models to schedule chemotherapy patients in cancer centers include [43][44][45][46].…”

Section: Deterministic and Stochastic Optimization In Outpatient Clinicsmentioning

confidence: 99%

Capacity Allocation in Cancer Centers Considering Demand Uncertainty

Keshtzari,

Norman

2024

Sci

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This paper introduces a model to aid decision-makers in answering many of the important questions regarding how best to operate a cancer center. This study aims to allocate the available cancer center capacity to different cancer types to minimize the deviation in patient demand satisfied from desired supply targets across multiple cancer types. A stochastic chance-constrained model is proposed to consider uncertainties in new and returning patient demand. The proposed model determines the optimal specialization mix for oncologists based on the distribution of demand by cancer type, preventing potential mismatches. Additionally, it aims to balance workloads among oncologists and individual clinics and indirectly reduce support service costs by limiting their clinic days. Numerical results are presented using historical data collected from our collaborating cancer center to demonstrate the usefulness of the model. The results confirm that the ability to satisfy patient demand increases as oncologists become more flexible. In addition, the results show that even having a small number of highly flexible oncologists is sufficient to achieve strong patient demand satisfaction. Moreover, restricting the allowable workload difference among oncologists achieves an acceptable trade-off between workload balance and satisfying patient demand.

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Section: Deterministic and Stochastic Optimization In Outpatient Clinicsmentioning

confidence: 99%

Capacity Allocation in Cancer Centers Considering Demand Uncertainty

Keshtzari,

Norman

2024

Sci

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“…The HS algorithm has been used in various applications, such as design optimization, image processing, and signal processing. Several modifications and extensions of the HS algorithm have also been proposed to improve its performance and applicability [62][63][64][65].…”

Section: Hsmentioning

confidence: 99%

CDDO–HS: Child Drawing Development Optimization–Harmony Search Algorithm

2023

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Child drawing development optimization (CDDO) is a recent example of a metaheuristic algorithm. The motive for inventing this method is children’s learning behavior and cognitive development, with the golden ratio being employed to optimize the aesthetic value of their artwork. Unfortunately, CDDO suffers from low performance in the exploration phase, and the local best solution stagnates. Harmony search (HS) is a highly competitive algorithm relative to other prevalent metaheuristic algorithms, as its exploration phase performance on unimodal benchmark functions is outstanding. Thus, to avoid these issues, we present CDDO–HS, a hybridization of both standards of CDDO and HS. The hybridized model proposed consists of two phases. Initially, the pattern size (PS) is relocated to the algorithm’s core and the initial pattern size is set to 80% of the total population size. Second, the standard harmony search (HS) is added to the pattern size (PS) for the exploration phase to enhance and update the solution after each iteration. Experiments are evaluated using two distinct standard benchmark functions, known as classical test functions, including 23 common functions and 10 CEC-C06 2019 functions. Additionally, the suggested CDDO–HS is compared to CDDO, the HS, and six others widely used algorithms. Using the Wilcoxon rank-sum test, the results indicate that CDDO–HS beats alternative algorithms.

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“…It can reach near-optimal solutions quickly and the performance of the patient-listing strategy is comparable to more complex scheduling strategies. Corsini et al [119] developed a hybrid harmonic search element heuristic algorithm to simulate a multi-stage chemotherapy ward to explore the problem of scheduling same-day chemotherapy outpatients to optimize patient waiting time. Ali et al [120] studied an integer planning model with a contraindicated search approach along with the addition of a simulation model solved in the ASs.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

A Review of Optimization Studies for System Appointment Scheduling

Niu,

Lei,

Guo

et al. 2023

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In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research.

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Hybrid Harmony Search for Stochastic Scheduling of Chemotherapy Outpatient Appointments

Cited by 5 publications

References 43 publications

Capacity Allocation in Cancer Centers Considering Demand Uncertainty

Capacity Allocation in Cancer Centers Considering Demand Uncertainty

CDDO–HS: Child Drawing Development Optimization–Harmony Search Algorithm

A Review of Optimization Studies for System Appointment Scheduling

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