Dynamic Scheduling in Inpatient Nursing

Cheng, Mingang; Ozaku, Hiromi Itoh; Kuwahara, Noriaki; Kiyokawa, Kiyoshi; Ota, Jun

doi:10.20965/ijat.2009.p0174

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…In our previous study, we proposed a dynamic scheduling method based on a simulated annealing algorithm (Cheng et al, 2008(Cheng et al, , 2009. Through the generation of an initial schedule in a static status and regenerating schedules when interruptions occur, the proposed method was proven effective for high-quality care provision throughout several simulated NSPs.…”

Section: Figure 1 Self-determined Inpatient Nursing -An Overview (Seementioning

confidence: 99%

“…As previously described (Cheng et al, 2009), a manual is modelled in a hierarchical way (Figure 3), with different layers connected by straight lines representing the activity by tasks and subtasks. Horizontal arcs indicate procedural constraints among tasks.…”

Section: Figure 2 Workheet -A Samplementioning

confidence: 99%

“…Through iterative recognition and instruction, the nurse was asked to provide nursing care to the patients. As previously described (Cheng et al, 2009), the proposed dynamic scheduling method divides scheduling into Phase 1, in which we consider performance optimisation based on earliness and tardiness as well as the makespan under static conditions to generate an initial schedule, and Phase 2, in which we address reactive scheduling to generate new schedules that accommodate interruptions and maintain the original anticipated performance even when the schedule is overloaded ( Figure 5). …”

Section: Inpatient Nursing Support Systemmentioning

confidence: 99%

“…Through modelling of the care into a set of nursing activities or tasks, subtasks and their starting and ending times, a nursing manual is created. As described in earlier work (Cheng et al, 2009), the provision of nursing care is organised according to the transition of positions, and therefore each nursing activity is classified into a set of nursing subtasks according to the position information. According to the starting time and ending time of the nursing subtasks of the above nursing activities, the statistical values (mean value and standard deviation) for the processing time of each nursing subtask were generated by applying the processing time analysis tool of nursing developed at the advanced telecommunications research institute international (ATR).…”

Section: Evaluation Of Task Processing Timementioning

confidence: 99%

See 3 more Smart Citations

Dynamic scheduling-based inpatient nursing support: applicability evaluation by laboratory experiments

Cheng¹,

Kanai‐Pak²,

Kuwahara³

et al. 2012

IJAACS

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The purpose of this study is to evaluate a dynamic scheduling-based nursing support system for nurses working in acute care. Due to unpredictable occurrences such as random disturbances from patients and the variability of processing times in nursing care, inpatient nursing in practical environments is complex. In this study, we implement a nursing support system in a series of laboratory experiments under simulated conditions. In the laboratory experiments, clinical nurses are asked to perform assigned nursing tasks and simulated patients are used to make the environment realistic. Our results show that, compared to the nurses' performance based on their own procedures (rules of action), the dynamic scheduling method resulted in an average improvement of 71% in terms of earliness or tardiness of care. The proposed dynamic scheduling-based nursing support system is proven to be highly applicable to nursing work in practical nursing care environments.

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Section: Figure 1 Self-determined Inpatient Nursing -An Overview (Seementioning

confidence: 99%

Section: Figure 2 Workheet -A Samplementioning

confidence: 99%

Section: Inpatient Nursing Support Systemmentioning

confidence: 99%

Section: Evaluation Of Task Processing Timementioning

confidence: 99%

See 2 more Smart Citations

Dynamic scheduling-based inpatient nursing support: applicability evaluation by laboratory experiments

Cheng¹,

Kanai‐Pak²,

Kuwahara³

et al. 2012

IJAACS

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Modeling the Process of Animation Production

Nakanishi¹,

Shichijo²,

Sugi³

et al. 2013

Int. J. Automation Technol.

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In this study, a work process model for animation production is developed. Interviews with animation studio workers and surveys of their working diaries and shot progress charts are conducted to create a framework for the work processes. The work hours necessary for each operation of the work project are expressed using a gamma function. Workers are classified into two categories, managers and animators, and their behavioral rules are modeled. To establish a rule for the determination of the operation sequence order for an animator to perform multiple work operations, four typical dispatching rules, often used in a scheduling theory, are selected, and the one that is closest to actual data is regarded as the rule that the animator actually follows. As a result of the analysis, it is found that the Earliest Due Date (EDD) and SLACK are closest to actual animators’ behavioral rules. Managers are also found to move the sub-deadline (a deadline of each operation) up about 30% earlier than the actual deadline. The knowledge we obtain is that, in order to realize better working conditions, animators should determine their operation sequence order by using SLACK, and managers should designate subdeadlines by keeping a balance between the prevention of deadline violation and the reduction of overtime work.

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A Novel Algorithm for Continuous Steel Casting Scheduling with Focus on Quality Property Constraint and Slab Width Maximization

Ogata¹,

Okubo²,

Nagai³

et al. 2015

Int. J. Automation Technol.

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This paper proposes a solution for casting scheduling, an important process in steel manufacturing. A constraint due to secular changes in quality properties, including slab property degradation in casting, and problems with evaluation indices for slab casting width for the improvement of productivity, are taken into account in the study. These factors have not been focused on in previous studies. In this study, the casting scheduling problem is divided into two. One problem involves determining a schedule frame for each slab, and the other is the problem of determining the slab width. To be more specific, after an initial solution for slab order is reached based on heuristics with the quality property constraint taken into account, a hierarchical solving method of determining the slab width is employed in accordance with the shortest path problem-solving method, and obtained solutions are improved using a simulated annealing technique. The simulation is performed with the data created from actual operation data and an initial solution that satisfies the constraint is derived. An improved solution is then obtained using the solution search technique.

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Dynamic Scheduling in Inpatient Nursing

Cited by 3 publications

References 10 publications

Dynamic scheduling-based inpatient nursing support: applicability evaluation by laboratory experiments

Dynamic scheduling-based inpatient nursing support: applicability evaluation by laboratory experiments

Modeling the Process of Animation Production

A Novel Algorithm for Continuous Steel Casting Scheduling with Focus on Quality Property Constraint and Slab Width Maximization

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