A hybrid genetic algorithm with 2D encoding for the scheduling of rehabilitation patients

Huynh, Nhat-To; Huang, Ying-Che; Chien, Chen–Fu

doi:10.1016/j.cie.2018.08.030

Cited by 19 publications

(6 citation statements)

References 26 publications

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“…Huang, Zheng and Chien [17] developed a system, equipped with a Graphical User Interface, which can generate the optimal schedules for rehabilitation patients to minimize waiting time and thus enhance service quality and overall resource effectiveness of rehabilitation facilities. More recently, Huyinh, Huang and Chien [18] further refined the algorithm in order to develop a hybrid genetic algorithm (GASA) that integrates genetic algorithm (GA) and simulated annealing (SA). Recently, Li and Chen [19] designed a genetic algorithm based on Waiting Time Priority Algorithm (WTPA) which was tested on a rehabilitation department.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

“…The rehabilitation scheduling process [17][18][19]24] (RSP) consists of planning patients' physiotherapy sessions inside a rehabilitation institute. Hospitals that may profitably make a practical use of such scheduling, including those managed by ICS Maugeri 1 that will provide benchmarks in this paper, deal with up to hundreds of patients with a team of just few tens of physiotherapists; so, it is of paramount importance to be able to assign patients to operators efficiently.…”

Section: Introductionmentioning

confidence: 99%

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A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling

Cardellini

Nardi

Dodaro

et al. 2021

Rules and Reasoning

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The rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several requirements and optimizations, e.g., patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation's needs.In this paper, we present a solution to rehabilitation scheduling based on Answer Set Programming (ASP), which proved to be an effective tool for solving practical scheduling problems. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution.

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Section: Related Work and Conclusionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling

Cardellini

Nardi

Dodaro

et al. 2021

Rules and Reasoning

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show abstract

“…Genetic algorithms (GAs) are population-based evolution algorithms which have been efficiently used for different optimization problems [13,14]. Several studies have applied GA to find the weights of neural networks.…”

Section: Introductionmentioning

confidence: 99%

An Approach for Designing an Optimal CNN Model Based on Auto-Tuning GA with 2D Chromosome for Defect Detection and Classification

Huynh

Nguyen

2023

Sustainability

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Defect detection and classification on the final products are necessary for the manufacturers to ensure the quality of the final product before delivering it to the end customers. With rapid changes in manufacturing technologies, most of the companies have changed their operation methods toward industry 4.0. On this road, developing an automatic detection system based on the surface images can enhance the productivity and ensure the quality of the product. However, only a few studies have developed the models for solving this problem. Due to its complicated structure and parameters, designing an optimal convolution neural network (CNN) is still a challenge. Thus, this study aims to propose an autotuning genetic algorithm with two-dimension chromosomes for designing an optimal CNN model efficiently. In particular, a two-dimension chromosome is developed to represent a CNN’s structure and parameters. To enhance the searching process, the crossover rate and mutation rate are tuned automatically according to the generation. A two-dimension crossover method is proposed to create offspring for selecting the next population. In addition, a case of ceramic textile manufacturing is constructed to validate the proposed approach. The accuracy of the proposed approach is up to 95.5 percent on the testing dataset.

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“…The rehabilitation scheduling process consists mainly of planning daily patients' physiotherapy sessions inside a rehabilitation institute, that hereafter we refer to as Rehabilitation Scheduling Problem (RSP) (Huang et al 2012;Huynh et al 2018;Li and Chen 2021;Schimmelpfeng et al 2012). Hospitals that may profitably make a practical use of such scheduling, including those managed by ICS Maugeri 1 , which will provide benchmarks in this paper, deal with up to hundreds of patients with a team of just few tens of physiotherapists; so, it is of paramount importance to be able to assign patients to operators, i.e., physiotherapists, efficiently.…”

Section: Introductionmentioning

confidence: 99%

Solving Rehabilitation Scheduling problems via a Two-Phase ASP approach

Cardellini¹,

Nardi²,

Dodaro³

et al. 2023

Preprint

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A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical and ethical requirements and optimizations, e.g., patient's preferences and operator's work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation's needs.In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding, and then add domain specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain specific optimizations.Under consideration in Theory and Practice of Logic Programming (TPLP).

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A hybrid genetic algorithm with 2D encoding for the scheduling of rehabilitation patients

Cited by 19 publications

References 26 publications

A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling

A Two-Phase ASP Encoding for Solving Rehabilitation Scheduling

An Approach for Designing an Optimal CNN Model Based on Auto-Tuning GA with 2D Chromosome for Defect Detection and Classification

Solving Rehabilitation Scheduling problems via a Two-Phase ASP approach

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