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IEEE 802.11ah, which is a wireless network protocol designed for Internet of Things (IoT), devised the Restrict Access Window (RAW) mechanism to tackle the collision problem. However, some RAW's slots may be overloaded; some RAW's slots may be lightly loaded or have no load because no stations (STA) allocated in these slots need to access channel. This work adopted (i) the Registered Backoff Time (RBT) mechanism such that each STA can register the backoff time for its future channel access in access point (AP) and (ii) the Claiming RAW mechanism such that STAs are allowed to notify AP that they have uplinked data to transmit. In this way, AP can (1) know which STAs have uplinked data to transmit and thus (2) re-schedule those STAs from the overloaded slots to the slots that (i) are underloaded or (ii) no STAs need to access channel based on STAs' RBTs in advance. As a result, the proposed Registration-based Regrouping for Load-Balance Channel Access (RRG-LBCA) method can achieve load balance among slots to increase the IEEE 802.11ah network's performance. The performance evaluation results shown that the proposed RRG-LBCA method can eliminate the collision situation and increase the aggregate throughput. [ABSTRACT FROM AUTHOR]

In real scheduling problems, unexpected changes may occur frequently such as changes in task features. These changes cause deviation from primary scheduling. In this article, a heuristic model, inspired from Artificial Bee Colony algorithm, is proposed for a dynamic flexible job-shop scheduling (DFJSP) problem. This problem consists of n jobs that should be processed by m machines and the processing time of jobs deviates from estimated times. The objective is near-optimal scheduling after any change in tasks in order to minimise the maximal completion time (Makespan). In the proposed model, first, scheduling is done according to the estimated processing times and then re-scheduling is performed after determining the exact ones considering machine set-up. In order to evaluate the performance of the proposed model, some numerical experiments are designed in small, medium and large sizes in different levels of changes in processing times and statistical results illustrate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Frequent delays will be experienced in the start-up of molten steel on the converter equipment during the steelmaking–continuous casting (SCC) production process due to the untimely supply of molten iron or scrap, which may cause conflicts between adjacent heat on the same equipment or in the same casting. The casting machine is cut off, resulting in the failure of the static scheduling plan. SCC production ladle re-scheduling is based on the premise that the production process path remains unchanged, the operation of adjacent heat on the converter and refining furnace does not conflict, and the casting of adjacent heat within the same casting is continuous. The ladle re-scheduling of steelmaking and continuous casting production aims at continuously casting many charges with the same cast and avoiding conflicts of adjacent charges on the same machine. This mechanism proposes a method of ladle re-scheduling in the production process of steelmaking–refining–continuous casting, which is divided into two parts: plan re-scheduling and ladle optimisation scheduling. Firstly, a re-scheduling optimisation model of the steelmaking and continuous casting production is built. This model aims at minimising the waiting time of all charges. The re-scheduling strategy of steelmaking and continuous casting production is proposed by interval processing time of charges and scheduling expert experience. This strategy is composed of two parts: re-scheduling charge decision and charge processing machine decision. Then, the first-order rule learning is used to select the optimisation target to establish the ladle optimal scheduling model. The ladle matching rules are extracted on the basis of the rule reasoning of the minimum general generalisation. The ladle optimisation scheduling method that consists of the optimal selection of the ladle and the preparation of the optimal path of the ladle is proposed. Ladle selection is based on the production process and adopts rule-based reasoning to select decarburised ladle after choosing dephosphorised ladle. Ladle path preparation, which is a multi-priority heuristic method, is designed to decide the path of the ladle from the converter to the refining furnace to the continuous casting machine. Finally, this mechanism was actually verified based on the large-scale data of a steel company in Shanghai, China. Results showed that the production efficiency of steelmaking-refining-continuous casting was improved. [ABSTRACT FROM AUTHOR]

Aim: To evaluate and document the impacts of re-scheduling codeine to a prescriptiononly medication in Australia in February 2018. Design: Prospective cohort study. Participants completed an on-line survey with a range of outcome measures at four time-points, once before codeine was re-scheduled (November 2017) and three times after the event: 1 month after (February 2018), 4 months after (June 2018) and 12 months after (February 2019). Setting: Australia. Participants: Participants were 260 Australians aged 18 years and above who reported regular over-the-counter (OTC) codeine use and, at the time of the study, were not engaged in treatment for codeine dependence. Measurements: Survey measures included estimates of daily average codeine use (mg) and overall daily average opioid use [calculated using an oral morphine equivalent daily dose (OMEDD, mg)], opioid use disorder with regard to codeine use (using a modified Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV), pain and pain self-efficacy, anxiety and depression and health service use. Findings: A reduction in total daily codeine use (mg) from 64.3 mg [95% confidence interval (CI) = 46.7-81.9] in November 2017 (baseline) to 27.6 mg (95% CI = 19.2-36.0) in February 2019 (final time-point) was observed. A decline in the proportion of participants who met criteria for an opioid use disorder was also evident, with 51.2% (n = 133) at baseline relative to 33.3% (n = 58) at the 12-month follow-up. This study had an overall participant retention rate of 67% at the final time-point. Conclusion: Re-scheduling codeine in Australia has been accompanied by significant reductions in codeine use and prevalence rates of opioid use disorder in a cohort of individuals who regularly use the medication, without apparent adverse impacts on pain or measures of anxiety and depression. [ABSTRACT FROM AUTHOR]

Rush orders are common events in enterprises that are utilizing make-to-order production strategy. They have multiple negative impacts to the production system such as higher product defect rate which corresponds to product quality drop, not meeting the due dates and cause customers' dissatisfaction, higher production costs, waste of materials and energy. This research work studies the problem of rescheduling semi-automated assembly lines in the era of Zero Defect Manufacturing and in the face of real time events such as rush orders. This is achieved by adding to the adopted dynamic scheduling tool an extra criteria evaluation layer which is incorporating to the measured criteria the importance of each individual order. The proposed approach is validated through a real life industrial case in the semiconductor domain. The simulation results showed that incorporating the orders importance every time re-scheduling is needed can produce better schedules by 5.615%. © 2020 The Authors, Published by Elsevier B.V. Peer review under the responsibility of the scientific committee of CIRP. [ABSTRACT FROM AUTHOR]

In contemporary manufacturing systems, re-scheduling of the production has become an unavoidable and critical phenomenon. There are many types of unexpected events, which can disrupt the normal operation of manufacturing systems. Therefore, the current research work focuses on identifying the critical reaction time for such events in order to keep productivity and costs at acceptable ranges. The events that are considered are defected part, new order and machine breakdown. Another factor that is studied and is linked with the reaction time is the number of re-schedules per day, because those can cause confusion and loss of productivity. [ABSTRACT FROM AUTHOR]

Background and aims: Globally, codeine is the most‐used opioid. In December 2016, Australia announced that low‐strength codeine (≤ 15 mg) would be re‐scheduled and no longer available for purchase over‐the‐counter; this was implemented in February 2018. We aimed to evaluate the effect of this scheduling change on codeine misuse and use and misuse of other opioids. Design and setting: Interrupted time–series analysis of monthly opioid exposure calls to New South Wales Poisons Information Centre (NSWPIC, captures 50% of Australia's poisoning calls), January 2015– January 2019 and monthly national codeine sales, March 2015–March 2019. We incorporated a washout period (January 2017 – January 2018) between the announcement and implementation, when prescriber/consumer behaviour may have been influenced. Participants: Intentional opioid overdoses resulting in a call to NSWPIC. Measurements We used linear segmented regression to identify abrupt changes in level and slope of fitted lines. Codeine poisonings and sales were stratified into high strength (> 15 mg per dose unit) and low strength (≤ 15 mg). Only low‐strength formulations were re‐scheduled. Findings We observed an abrupt −50.8 percentage [95% confidence interval (CI) = −79.0 to −22.6%] level change in monthly codeine‐related poisonings and no change in slope in the 12 months after February 2018. There was no increase in calls to the NSWPIC for high‐strength products, level change: –37.2% (95% CI = −82.3 to 8%) or non‐codeine opioids, level change: –4.4% (95% CI = −33.3 to 24.4%). Overall, the re‐scheduling resulted in a level change in opioid calls of −35.8% calls/month (95% CI = −51.2 to −20.4%). Low‐strength codeine sales decreased by 87.3% (95% CI = −88.5 to −85.9%), with no increase in high‐strength codeine sales in the 14 months following re‐scheduling, −4.0% (95% CI = −19.6 to 14.6%). Conclusions: Codeine re‐scheduling in Australia appears to have reduced codeine misuse and sales. [ABSTRACT FROM AUTHOR]

Despite the high automatization that characterizes modern production, human operators still hold a vital position in manufacturing, which should be reinforced in the transition to the era of Industry 4.0. As human operators may support increased flexibility and adaptability to their tasks, they gain an advantage in highly customized productions, where products' configuration and tasks allocated per workstation may be dynamically changed. In order to support dynamic knowledge transfer to the human operators in a way that is perceivable and does not limit operators' capabilities, it is important to exploit novel visualization technologies introduced by Industry 4.0. This paper presents an automated approach for remotely supporting assembly workstations, with human operators using augmented reality technology. The system retrieves the workstation's schedule and automatically generates assembly instructions, utilizing information from the product's design, enriched with order-specific annotations based on product customization. Then, the generated augmented reality instructions are transmitted through a cloud environment to the assembly station operator, aiming to support dynamic production re-scheduling. The developed system is validated in a real-life case study provided by the automotive industry. [ABSTRACT FROM AUTHOR]

Grid computing enables large-scale resource sharing and collaboration for solving advanced science and engineering applications. Central to the grid computing is the scheduling of application tasks to the resources. Various strategies have been proposed, including static and dynamic strategies. The former schedules the tasks to resources before the actual execution time and later schedules them at the time of execution. Static scheduling performs better but it is not suitable for dynamic grid environment. The lack of dedicated resources and variations in their availability at run time has made this scheduling a great challenge. In this study, we proposed the adaptive approach to schedule workflow tasks (dependent tasks) to the dynamic grid resources based on rescheduling method. It deals with the heterogeneous dynamic grid environment, where the availability of computing nodes and links bandwidth fluctuations are inevitable due to existence of local load or load by other users. The proposed adaptive workflow scheduling (AWS) approach involves initial static scheduling, resource monitoring and rescheduling with the aim to achieve the minimum execution time for workflow application. The approach differs from other techniques in literature as it considers the changes in resources (hosts and links) availability and considers the impact of existing load over the grid resources. The simulation results using randomly generated task graphs and task graphs corresponding to real world problems (GE and FFT) demonstrates that the proposed algorithm is able to deal with fluctuations of resource availability and provides overall optimal performance.

One common problem among Small and Medium Enterprises (SME) is to don’t have at disposal formal and simple approaches for production scheduling, especially in case of an event that introduces the requirement of a re-planning. The paper approaches this kind of event-driven re-scheduling problems at the arrival of a new order, when some jobs are under processing, some operation have already finished and other jobs are waiting to be loaded on a machine. For a simple application in a SME, to the operations already started and completed for a job a processing time equal to zero is assigned; the operations already started but not yet completed are interrupted and considered as operations that must be executed for the remaining part of their processing time; all the other jobs are considered for the event-driven job-shop re-scheduling problem. A validation of the procedure in a realistic application is presented. [ABSTRACT FROM AUTHOR]

In this work we consider the problem of selecting a set of patients among a given waiting list of elective patients and assigning them to a set of available operating room blocks. We assume a block scheduling strategy in which the number and the length of available blocks are given. As each block is related to a specific day, by assigning a patient to a block his/her surgery date is fixed, as well. Each patient is characterized by a recommended maximum waiting time and an uncertain surgery duration. In practical applications, new patients enter the waiting list continuously. Patient selection and assignment is performed by surgery departments on a short-term, usually a week, regular base. We propose a so-called rolling horizon approach for the patient selection and assignment. At each iteration short-term patient assignment is decided. However, in a look-ahead perspective, a longer planning horizon is considered when looking for the patient selection. The mid-term assignment over the next $$n$$ weeks is generated by solving an ILP problem, minimizing a penalty function based on total waiting time and tardiness of patients. The approach is iteratively applied by shifting ahead the mid-term planning horizon. When applying the first week solution, unpredictable extensions of surgeries may disrupt the schedule. Such disruptions are recovered in the next iteration: the mid-term solution is rescheduled limiting the number of variations from the previously computed plan. Besides, the approach allows to deal with new patient arrivals. To keep limited the number of disruptions due to uncertain surgery duration, we propose also a robust formulation of the ILP problem. The deterministic and the robust formulation based frameworks are compared over a set of instances, including different stochastic realization of surgery times. [ABSTRACT FROM AUTHOR]

This study addresses the scheduling problem in remanufacturing engineering. The purpose of this paper is to model effectively to solve remanufacturing scheduling problem. The problem is modeled as flexible job-shop scheduling problem (FJSP) and is divided into two stages: scheduling and re-scheduling when new job arrives. The uncertainty in timing of returns in remanufacturing is modeled as new job inserting constraint in FJSP. A two-stage artificial bee colony (TABC) algorithm is proposed for scheduling and re-scheduling with new job(s) inserting. The objective is to minimize makespan (maximum complete time). A new rule is proposed to initialize bee colony population. An ensemble local search is proposed to improve algorithm performance. Three re-scheduling strategies are proposed and compared. Extensive computational experiments are carried out using fifteen well-known benchmark instances with eight instances from remanufacturing. For scheduling performance, TABC is compared to five existing algorithms. For re-scheduling performance, TABC is compared to six simple heuristics and proposed hybrid heuristics. The results and comparisons show that TABC is effective in both scheduling stage and rescheduling stage. [ABSTRACT FROM AUTHOR]

Objective The study aims to evaluate factors influencing pharmacists' management of eye infections following the reclassification of ophthalmic chloramphenicol to pharmacist supply. Methods Data were collected using a self-administered questionnaire posted to a random sample of community pharmacies in urban and rural areas in Western Australia. Data were entered into Excel and analysed using SPSS v17 (SPSS Inc., Chicago, IL, USA) and SAS v9.2 (SAS Institute Inc., Cary, NC, USA). Descriptive statistics were used to summarise the responses and demographics of respondents. Regression analysis was used to identify relationships between variables. Factor analysis was conducted to pool variables and the derived factors were subjected to regression analysis. Key findings Of the 240 community pharmacies surveyed, 119 (49.5%) responded (79% urban and 21% rural pharmacies). Urban and rural pharmacies provided ophthalmic chloramphenicol over-the-counter ( OTC) 3-4 and 1-2 times weekly, respectively ( P = 0.021), with some pharmacies providing 12 or more per week. Over 82% of respondents claimed that sales of other OTC products used for acute bacterial conjunctivitis had 'decreased/decreased markedly'. A majority of respondents (59%) claimed that there was no change in the number of prescriptions received for ophthalmic chloramphenicol. Most respondents (76.4%) agreed/strongly agreed that pharmacist's current level of training was adequate to provide ophthalmic chloramphenicol. However, approximately one-fifth (21.8%) responded that pharmacists required some additional training. Conclusions Down-scheduling of ophthalmic chloramphenicol has improved pharmacists' capability to treat acute bacterial conjunctivitis, largely as a replacement for products previously available OTC, rather than fewer general practitioner consultations. Pharmacists showed overall support for the reclassification as it enabled better use of professional skills and patient access to improved treatment options. [ABSTRACT FROM AUTHOR]

Abstract: Short-term variations in wind power generation make real-time balancing of load and generation a more challenging task for the Transmission System Operator (TSO). One issue of interest that could facilitate the efficient integration of wind power is to shift larger parts of the balancing responsibility from the TSO to the power generating companies. The idea is to reduce the real-time balancing need for the TSO by demanding power generating companies to minimise their expected imbalances. To comply with this, power generating companies can re-schedule their production based on updated production forecasts. As a key of the contribution, this paper analyses internal ex-ante self-balancing, where this re-scheduling is done shortly before the period of delivery and internally within each power generating company. To quantify the value of such a more distributed balancing responsibility, a model has been developed which consists of a sequence of optimisation models. Then, possible trading decisions of power generating companies are evaluated in different situations. This is based on a hydro-thermal generation portfolio within the framework of the Nordic electricity market. [Copyright &y& Elsevier]

Abstract: There is plenty of evidence that drivers may make small changes in their time of travel to take advantage of lower levels of congestion. However, progress in the practical modelling of such “micro” re-scheduling within peak period traffic remains slow. While there exist research papers describing theoretical solutions, techniques for practical use are not generally available. Most commonly used assignment programs are temporally aggregate, while packages which do allow some “dynamic assignment” typically assume a fixed demand profile. The aim of the paper is to present a more heuristic method which could at least be used on an interim basis. The assumption is that the demand profile can be segmented into a number of mutually exclusive “windows” in relation to the “preferred arrival time”, while on the assignment side, independently defined sequential “timeslices” are used in order to respect some of the dynamic processes relating to the build-up of queues. The demand process, whereby some drivers shift away from their preferred window, leads to an iterative procedure with the aim of achieving reasonable convergence. Using the well-known scheduling theory developed by Vickrey, Small, and Arnott, de Palma & Lindsey, the basic approach can be described, extending from the simple “bottleneck”, to which the theory was originally applied, to a general network. So far, insufficient research funds have been made available to test the approach properly. It is hoped that by bringing the ideas into the public domain, further research into this area may be stimulated. [Copyright &y& Elsevier]

Abstract: With the increasing traffic volumes in European railway networks and reports on capacity deficiencies that cause reliability problems, the need for efficient disturbance management becomes evident. This paper presents a heuristic approach for railway traffic re-scheduling during disturbances and a performance evaluation for various disturbance settings using data for a large part of the Swedish railway network that currently experiences capacity deficiencies. The significance of applying certain re-scheduling objectives and their correlation with performance measures are also investigated. The analysis shows e.g. that a minimisation of accumulated delays has a tendency to delay more trains than a minimisation of total final delay or total delay costs. An experimental study of how the choice of planning horizon in the re-scheduling process affects the network on longer-term is finally presented. The results indicate that solutions which are good on longer-term can be achieved despite the use of a limited planning horizon. A 60min long planning horizon was sufficient for the scenarios in the experiments. [Copyright &y& Elsevier]

A letter to the editor is presented in response to the article "The impact of codeine rescheduling on misuse: a retrospective review of calls to Australia's largest poisons centre," by Cairns et al. and printed in a 2016 edition of the periodical/