In most Japanese hospitals, different nurses handle the pre-assigned nursing cares in different ways, which directly affect the quality of nursing cares. To our knowledge, there has been less attention on ensuring that nurses provide nursing cares in a timely and accurate fashion. Consequently, in this paper, considering the similarities to the traditional job shop scheduling problems, we will model the daily nursing care scheduling problems and propose an efficient scheduling method based on simulated annealing algorithm. By iteratively local searching based on simulated annealing: (1) permutating the tasks from one nurse to another and (2) permutating the sub tasks handled by a nurse from its original position to another new one, the proposed method is evaluated to be applicable to the nursing care scheduling problems (providing comprehensive, coordinated and cost effective nursing cares to patients).
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.
Nursing, with the primary mission to provide quality services to patients, is accompanied by a serial of activities like patients assessment, outcomes identification for patients. In general, there has been less attention on ensuring that nurses provide nursing cares in a timely and accurate fashion. Consequently, in this paper, considering the similarity to the traditional job shop scheduling problems, we will model the daily nursing care scheduling problems and propose an efficient scheduling method based on simulated annealing algorithm. By the comparison of several nursing care plans obtained by the dispatching-rule based methods (which have been recognized to be the implementation of human thoughts), the proposed method is evaluated to be applicable to the nursing care scheduling problems (providing comprehensive, coordinated and cost effective nursing cares to patients).
To shorten the notoriously long waits for service in hospitals in Japan and to improve efficiency, we propose a scheduling algorithm with a 2-layer local search based on simulated annealing -- permutating (switching) (i) tasks among nurses and (ii) subtasks on each nurse. The scheduling algorithm generates a solution initializing our proposed dynamic scheduling to iteratively generate new, feasible schedules based on the scheduling algorithm to accommodate interruptions while preventing nurses' work hours from increasing. To verify the effectiveness of our proposed scheduling, we executed a set of nursing scheduling problems taken from those actually observed and focused on those that featuring frequent interruptions.
Nursing, with the primary mission to provide quality services to patients up to 24 hours a day, is accompanied by a serial of activities like patients' assessment, outcomes identification, etc. As we know, hospitals with lower nurse staffing levels tend to have higher rates of poor patient outcomes. However, increasing staffing levels is not yet an easy task. Therefore, an online nursing scheduling system is practically mandatory to instruct nurses' actions for high-quality nursing cares. In general, major difficulties contributing to propose an effective scheduling system include the nurse action rules and necessary reference information. In this respect, we illustrate the ways of nurses to handle their works from the viewpoint of scheduling in this paper. By hypothetically modelling the action rules as some traditional dispatching rules, we analyse the difference of nursing staffing levels (especially between nurse experts and novices). Implementing a set of traditional dispatching rules on several actual nursing cares, this paper concludes the closest ones to nurses' action rules. It also concludes that nurse experts consider the preparation tasks more, and handle them with a slack time.
In semiconductor manufacturing, rescheduling problems are extremely difficult to solve in real time due to the high frequency of disturbances that occur approximately every minute. This paper proposes a new approach to online manufacturing rescheduling. Unlike the traditional methods to have a scheduling process again, we (1) revise the existing schedule to keep high schedule stability based on message passing rescheduling with operation sorting; and (2) during the manufacturing process, improve the performance of the revised schedule with the introduction of a quick local search on semi-critical paths. In actual problems with about 200,000 processes, this method can effectively accommodate disturbances in less than 1 second, and a better schedule can be obtained in less than 1 minute. This method has been demonstrated to be more effective than conventional dispatching-rule methods, some of which have been actually applied in many facilities, because it offers higher schedule stability and fewer violations of due dates.
Semiconductor manufacturing is mainly characterized by diversity of products, different process types, and random failures. It is extremely difficult to solve scheduling problems due to high frequency of disturbance occurrence. This paper proposes a new approach for the online manufacturing rescheduling method. Instead of having a dispatching process based on dispatching rules once again, we revise the existing schedule based on message passing principle once the disturbance occurs, and improve the performance of the revised schedule by the introduction of a quick local search according to permutations of processes on semi-critical paths. The proposed method can release the influence of disturbances in less than 1 second, and finish rescheduling process in less than 1 minute. Through the actual problems with about 200,000 processes, this method is evaluated to be more effective for actual manufacturing than the dispatching-rule based methods, some of which have been applied in many facilities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.