Optimal Shift Schedule Research Articles

APPLICATION OF 0-1 INTEGER GOAL PROGRAMMING FOR SHIFT SCHEDULING OF MEDICAL STAFF IN LABORATORY DEPARTMENT

With the increase in population, hospitals are the institutions with the most intensive shift work. When scheduling shifts in hospitals, it is difficult to create a balanced shift schedule for each staff by taking into account constraints such as the working conditions of the hospital, the satisfaction of patients, staff and the hospital, and the wishes of staff in terms of days off, holidays , etc. as well as different objectives. The aim of this study is to optimally plan the shift schedule for medical staff in the laboratory department. The shift schedule of the laboratory department of a government hospital in Gümüşhane in November 2022 was used for the study. According to the working conditions and shift schedule of the hospital, a 0-1 integer goal programming model is established. The optimal shift schedule was obtained as a result of analyzing the model by coding it in the GAMS 42.5.0 program.

Coordinated clutch actuation for drivability improvement and energy management of a novel multi-mode hybrid electric vehicle and HIL validation

This article presents a novel architecture of a particular class, i.e., multi-mode hybrid electric propulsion systems that utilize two planetary gear sets, multiple clutches, two electric motors, and an internal combustion engine. Although this class of propulsion systems offers architectural compactness, improved fuel economy, and operational versatility, it faces a drivability issue arising from simultaneous clutch engagement and disengagement during mode shift events. Such drivability issues cannot be addressed by baseline motor-torque compensation-based coordinated control that is typically employed to address the drivability issues in power-split and parallel hybrid propulsion systems. Therefore, this article proposes an enhanced version of the coordinated control that includes the clutch’s torque capacity control. The enhanced coordinated control module augments with the energy management system, making the mode shift schedule drivable and near-optimal. A real-time hardware-in-the-loop test bench is developed to accurately evaluate the enhanced coordinated control’s impact on the energy management system’s performance. Test bench results demonstrate that the enhanced coordinated control is more effective than the baseline coordinated control in attenuating the propulsion system’s perturbations during mode shift events and making the overall mode shift schedule drivable. The enhanced energy management system consumes 7%–8% more fuel while transforming the mathematically optimal mode shift schedule into a drivable one.

Coordinated control strategy for braking and shifting for electric vehicle with two-speed automatic transmission

This paper presents a coordinated control strategy for braking and shifting of electric vehicles that are equipped with a two-speed automatic transmission. The coordinated control strategy mainly includes braking force distribution and synthetic shifting regulation for braking operations. Firstly, the vehicle model is established for investigation of the shift process during braking. Then, the braking force distribution considering energy efficiency is presented, and the regenerative braking force is calculated. With the target of maximizing energy recovery and ensuring driving comfort, an optimal shift schedule during regenerative braking is advanced based on the multi-objective cuckoo search algorithm. Due to the interaction of regenerative braking force in torque releasing and restoring process, an adaptive braking mode switching control is proposed to improve the shifting smoothness. The detailed simulations and hardware-in-the-loop validations are conducted to verify the anticipated performance of the proposed strategy.

Adverse Health Effects Related to Shift Work Patterns and Work Schedule Tolerance in Emergency Medical Services Personnel: A Scoping Review.

Paramedicine as a profession is continually evolving in clinical practice, responsibilities, and workload. Changes over time in both population demographics and distribution have altered the demand for, and availability of, prehospital emergency medical services (EMS). These factors may also affect scheduling policies in many EMS organizations. However, there is little evidence that suggests optimal shift scheduling patterns to reduce adverse health events such as increased stress or fatigue in prehospital emergency health care providers. Our objective was to describe associations between variations in shift scheduling patterns and EMS provider health outcomes, such as fatigue, stress, sleep quality, and general mental and physiological health. We also sought to identify knowledge gaps. We performed searches of PubMed, CINAHL, Embase, and Cochrane databases for primary studies, systematic reviews, and meta-analyses published between January 2000 and December 2020. Studies reporting measurable health care outcomes in prehospital personnel with defined shift schedule patterns in land-based ambulance systems were included. Our search strategy yielded 188 studies, of which 11 met eligibility criteria (eight cross-sectional surveys, one single case report, one retrospective cohort study, one prospective cohort study, and one systematic review), with one additional study found through reference list screening, leaving 12 studies for review. All publications contained a description of shift schedule characteristics and shared similar outcomes of interest, although there was variation in comparators and assessment of outcomes. Most studies showed high rates of fatigue, stress, mental health concerns, and negative general health outcomes in paramedic shift worker populations. The case study reported improved fatigue, alertness, and sleep quality levels following a switch from a 24-hour shift pattern to an eight-hour shift. We did not complete an in-depth risk of bias assessment for any of the studies. Melnyk evidence ratings varied from IV to VI, indicating a low quality of evidence evaluating the impacts of shift schedule patterns in paramedics, with the retrospective cohort study design, ranked as IV, systematic review as a V, and prospective cohort study, case report and surveys ranked as VI. The low quality and quantity of evidence indicate the need for further research to definitively assess relationships between specific schedule patterns and health outcomes.

Shift Scheduling Optimization: A Real-Life Underground Transportation Example

Personnel scheduling is basically a type of scheduling that determines which employee will work and when, taking into account the needs of the industry and employees. Personnel scheduling is intertwined with shift scheduling problems in shift systems. In many industries, the assignment of employees to shifts during the day, the determination of relief breaks and meal breaks are an important factor for shift scheduling while meeting the changing workforce needs. The main purpose of this study is to schedule the shifts of the machinists of Ankaray, which is one of the underground transportation networks of Ankara, the capital of Turkey, in the transportation sector where people serve people. In the study, shift scheduling models in the literature were examined and Aykin's optimal shift scheduling with multiple break windows was taken as a basis. The model divides the working hours into two shifts during the day and finds the number of employees required for each shift. In addition, it also determines the relief break and lunch break times for each employee. As a result, the current situation was analyzed and a comparison was made with the results on the established optimization model. Cost minimization is at the root of the problem, so it is concretely shown how this model will contribute in real life.

Multi-parameter predictive shift schedule of automatic mechanical transmission for electric bus

Shift schedule is crucial in improving the dynamic and economic performance of electric vehicles (EVs) equipped with automatic mechanical transmission (AMT). As the driver, vehicle, and road constitute a closed-loop inseparable system, identifying the states of both vehicle and road is fundamental to realizing optimal shift schedule. However, the existing shift strategies neglect the coupling relationship of multiple parameters to the shift strategy. To minimize this gap, this paper presents a novel multi-parameter shift schedule based on model predictive control. Firstly, cubature Kalman filters (CKF) algorithm is employed to accurately estimate vehicle quality and road slope, which could improve the energy economy of EVs. Secondly, an artificial neural network (ANN) is adopted to forecast the compound future short horizon driving conditions, which contains the perdition information of vehicle velocity and road slope. Meanwhile, the AMT predictive shift schedule based on the above estimated and forecast information is constructed, which used dynamic programming to optimize in the rolling horizon. Simulation study results indicate that the ANN-based predictive approach shows better performance on accuracy and robustness than that of Markov chain, and the electricity consumption over China typical urban driving cycle (CTUDC) is further reduced by 6.79% than that of multi-parameter rule-based shift schedule.

Optimal sizing and energy management of an electric vehicle powertrain equipped with two motors and multi-gear ratios

This paper aims to fully exploit the superior advantages in improving energy economy and dynamic performance of an electric vehicle powertrain equipped with two motors and multi-gear ratios. Considering the dependence of gear ratio selection on motor sizing, a two-loop optimization algorithm, combined by the global search method and non-dominated sorting genetic algorithm-II, is proposed to find optimal motor sizes and transmission ratios. An energy management strategy with novel shift schedules based on the equivalent efficiency of two motors, current engaged gears, and driving conditions is then recommended. The energy management strategy also optimizes the torque allocation to two motors to minimize electricity consumption. Subject to the total of motor peak powers being constant, simulation results for a case study of urban bus show that the optimization of both motor sizes and gear ratios considerably enhances the energy efficiency of powertrain system. In comparison with a single-motor powertrain, optimal motor scales of larger than 0.42 and corresponding gear ratios reduce the electricity consumption significantly by 4.82−5.08%. Besides, the introduced energy management strategy with optimal shift schedules is proved to ensure comparably maximum efficiency while effectively preventing unnecessary and repeated gear changes.

Rotating between day and night shifts: Factors influencing sleep patterns of hospital nurses.

This study aimed to investigate sleep patterns of hospital nurses using a wearable electronic device and determine the influence of rotating day and night shifts and lifestyle factors on their sleep efficiency. Nurses working in shifts are vulnerable to sleep disturbances. However, little is known about the influence of rotating day and night shift schedules and healthy lifestyle on nurses' daily sleep patterns. Descriptive correlational design. Thirty-two hospital nurses working in shifts and 32 hospital nurses not working in shifts participated in data collection. Their sleep patterns were measured for six consecutive days using Fitbit Charge 3™ , and information on alcohol consumption, exercise, and eating habits were assessed using a questionnaire. Data were analysed using repeated measures analysis of variance with post hoc Scheffe's test and hierarchical multiple regression analysis. The study was conducted in accordance with the STROBE guideline. Overall, nurses working on rotating day and night shifts had significantly shorter total sleep time, longer sleep onset latency, and lower sleep efficiency than those not working in shifts. In particular, nurses working for 3 or 4 consecutive night shifts had significantly shorter total sleep time, lower sleep efficiency and longer sleep onset latency than those working for 0-2 consecutive night shifts. Rotating day and night shifts and alcohol consumption significantly influenced sleep efficiency. A work schedule of ≥3 consecutive night shifts and the habit of alcohol consumption before bed time influence nurses' sleep efficiency. Given the poor sleep pattern among nurses working in shifts, particularly those working on ≥2 consecutive night shifts, it is necessary to develop an optimal shift schedule and a program to promote healthy lifestyle among hospital nurses.

Optimization and coordinated control of gear shift and mode transition for a dual-motor electric vehicle

The electric vehicle equipped with dual motors and four-speed automated manual transmission has demonstrated its superiority in improving energy efficiency and dynamic performance. To exploit this configuration effectively, optimal shift schedules and corresponding mode selection maps are proposed separately for accelerating and braking conditions. Hysteresis zones between upshift and downshift lines are created by properly integrating a priority factor into the equivalent motor efficiency. Interestingly, the proposed shift schedules depend not only on the motor efficiency map, motor torque allocation, but also on the current working gear pair. Besides, the intersections of the shift schedules and mode selection borders show that gear shift and mode transition need to be implemented at the same time. Therefore, a coordinated control strategy is developed to handle these requirements. Finally, simulation results show that the case of without hysteresis zones achieves minimum electricity consumption but with many undesired and unnecessary gear changes. Conversely, with comparable energy economy, the introduced priority factor of 0.02 avoids the shift hunting effectively. Moreover, taking the advantages of the powertrain configuration, the proposed coordinated control strategy eliminates all torque gaps under the gearshift and mode transition, so great shift quality is achieved.

An Integrated Shift Schedule Assessment and Selection Procedure for Power & Water Plants in Kingdom of Bahrain

Abstract The continues increase in population and market globalization necessitated offering additional services and mass production strategy deployment. Consequently, a dramatic increase in research studies have been directed towards mitigating the shift schedule harmful physical, psychological, and social life effects on the workers. In addition, studies are currently conducted to determine the optimal shift schedule and shift rota, which is capable to incorporate human factors and applicable to the environment adopted in. In Kingdom of Bahrain there are no studies that investigate the effects of shift schedule on the operators, neither provide clear guidelines to select the appropriate shift schedule based on the environment adopted in. Accordingly, the aim of this paper is to present the development of an effective shift schedule selection mechanism that considers the physical, psychological, and social life factors for Al-Dur Power and Water Plant in Kingdom of Bahrain. The research methodology adopted was based on survey and case study. The results of this research study concluded that the shift schedule selection procedure developed was capable to involve all the stakeholders associated in the shift schedule selection process. In addition, it based the assessment and decision on the work environment adopted in.

Optimal energy management and shift scheduling control of a parallel plug-in hybrid electric vehicle

This paper deals with design of a control strategy for a parallel powertrain configuration of a plug-in hybrid electric vehicle (PHEV). The control strategy is aimed at minimising fuel consumption and number of gear shift events for a wide range of driving cycles, while keeping the battery state-of-charge within allowable range. A control-oriented backward-looking model of PHEV powertrain is used as a design basis. The control strategy combines a rule-based controller with an equivalent consumption minimisation strategy (ECMS). The ECMS uses both transmission gear ratio and engine torque as control variables, thus eliminating a need for designing a separate gear shift scheduling strategy and exploiting a full potential of powertrain efficiency improvement. The overall control strategy is designed for different characteristic operating regimes including charge depleting, charge sustaining, and blended regimes. The strategy is verified by computer simulations against globally optimal benchmark obtained by using the dynamic programming-based optimisation, whose results are also used for fine tuning of controller parameters.

Optimal energy management and shift scheduling control of a parallel plug-in hybrid electric vehicle

Optimal energy management and shift scheduling control of a parallel plug-in hybrid electric vehicle

Human resource management: new approach to nurse scheduling by considering human error

Human error is a critical concern in healthcare systems from primary care clinics to operating rooms in hospitals. Prevention or reduction of the chance of occurrence of such errors through increasing human reliabilities is tremendously important and deserves to be focused within personnel scheduling problems in healthcare systems. The present study is to develop a new multi-objective integer mathematical model which includes human errors of nurses to determine optimal shift scheduling of nurses. In addition to medical errors, several constraints in real-world problem including “minimum number of available nurses in each shift”, “restrictions on shift rotation for each nurse”, and “Minimum and maximum working hours in a week” are also taken into account. Nurses’ preference score, allocation costs, penalty cost of violating soft constraints, and human errors are all considered as objectives to be optimized. The multi-objective model, developed in this study, is solved by employing the weighted-sum method. To verify and validate the proposed model, a test problem is also solved. Sensitivity analysis on the model indicates that the solution method can reach acceptable solutions within an acceptable time. The present study is to help decision-makers to achieve optimal scheduling for decreasing costs and improving safety in healthcare systems. Based on this approach, decision makers can totally minimize the number of errors by considering the number of nurses required in each grade as well as proper allocation of them to different work shifts.

Association between irregular menstrual cycles and occupational characteristics among female workers in Korea

ObjectiveTo examine the association between irregular menstrual cycles and occupational characteristics among Korean female workers. Study designWe analyzed data on paid female workers from the Korea National Health and Nutrition Examination Survey (KNHANES) V (2010–2012). Main outcome measuresWe evaluated the possible associations between irregular menstrual cycles and work variables (occupational classification, working hours, and shift work) using univariate and multivariate logistic regression analyses. Weighted prevalence was calculated according to each work variable to approximate the Korean population. ResultsIrregular menstrual cycles were the most common in women in the ‘pink collar’ group (16.61%). The frequency of irregular menstrual cycles was 2-fold higher in women working >60 h per week (25.64%) than in those working 20–60 h per week (11.09%). Irregular menstrual cycles were more prevalent in shift workers (15.85%) than in non-shift workers (11.06%). A significantly high risk of irregular menstrual cycles was found for pink-collar occupations (adjusted odds ratio [OR] = 1.687, 95% confidence interval [CI] = 1.044–2.710, reference: white-collar occupation group) and in women with long working hours (adjusted OR = 2.139, 95% CI = 1.243–3.559, reference: 20–60 working hours group) and shift work (adjusted OR = 1.487, 95% CI = 1.028–2.118, reference: fixed working schedule group). ConclusionsOur study showed associations between irregular menstrual cycles and occupational characteristics of female workers. Long working hours, shift work, and pink-collar occupations are positively associated with irregular menstrual cycles. Therefore, working hours and shift schedules for female workers should be structured considering these factors. Further research is needed to determine the optimal working time and shift schedules for female workers.

Blending gear shift strategy design and comparison study for a battery electric city bus with AMT

To improve the performance of heuristic strategy used in most of the electric city buses equipped with automated manual transmission (AMT) currently, this paper proposes a systematic blending extraction method to optimize and accelerate the shift schedule design process. The crucial related factors, including the shift time, transmission efficiency and various driving cycle features, are considered to assure the online practicability. Dynamic programming (DP) algorithm is applied over featured velocity profiles to explore the global optimal operating points offline. Then k-means clustering algorithm is adopted to extract the explicit optimal shift schedule, where the number of centroids is determined by hierarchical analysis process and a new distance calculation method is performed considering proper weighting factors to blend the shift points from different driving conditions. The stochastical driving cycle is generated randomly from the previous data and is used to validate the comprehensive performance by chassis dynamometer tests. A comparison study is conducted among the proposed and conventional shift strategies. Experimental results demonstrate that the extracted blending strategy can improve the energy consumption significantly and is proved to be efficient, flexible, and online implementable compared to the other strategies.

Analysis of Optimal Shift Schedule Derivation for Electric City Buses Equipped with Automatic Manual Transmission

Since most of the electric city buses equipped with automated manual transmission (AMT) are currently implemented with a heuristic strategy, this paper proposes a systematic extraction method to optimize and accelerate the shift schedule design process. A dynamic model of the electric city bus with a four-speed AMT is established to study the energy management strategy. Dynamic programming (DP) algorithm is adopted to explore the offline global optimal control sequence considering the shift frequency. Then the feature of optimal operating points is analyzed and a time-saving derivation methodology is discussed to construct the gear shift schedule based on the clustering algorithm. The derived control strategy is proved to be efficient, flexible and online implementable. Simulation results show that the derived strategy can improve the energy economy by 4.45% compared with the preliminary empirical gear shift schedule, which is 57.8% better than back-propagation neural networks in a determined city route.

Study on Optimal Power Shift Schedule of Self-propelled Combined Harvester

In terms of the optimal power shift schedule of combined harvesting machinery, in order to improve the accuracy on solving optimal power shift points, this paper deduces the solving method to obtain the optimal power shift law of harvesting machinery based on the analyzing the characteristics of harvesting machinery. Two shift control parameters that have significant impacts on the optimal power shift point of harvesting machinery are put forward in the paper, namely the mass parameter and power distribution parameter. Taking the 4YZ-4- type combined maize harvester as an example, through the numerical calculation of MATLAB, it is found out that the change of mass parameter and power distribution parameters have significant impacts on the optimal power shift point. When the quality of harvesting machinery increases, the speed of the optimal power shift point will increase and the acceleration will decrease. When the power distribution coefficient of the driving axle of the harvesting machine increases, the corresponding speed at the optimal power shift point will decrease and the corresponding acceleration will increase.

Look-ahead gear-shifting strategy on ramps for heavy trucks with automated mechanical transmission

Look-ahead information has been applied to vehicle shift systems and has led to the development of innovative changes in shifting strategies. A shifting strategy significantly influences the dynamic and economic performance of a truck. If a shift control system can predict the information of the road ahead, then the dynamic programming method can be used to obtain an optimal shift schedule, thereby achieving the best balance between the dynamic and the economic performance of a truck. Determining the weights of the economic and dynamic performance of a truck is critical in dynamic programming. Weight is related to road slope value; hence, this study uses different weights on 3%, 5%, and 10% ramp simulation experiments to investigate the relationship between fuel consumption and running time and to determine the optimum weight for different slopes. On the basis of the optimal shift schedule obtained via dynamic programming, the ramp information of the road ahead can be utilized to adjust the shift point to avoid unnecessary shifting before entering the slope and reduce shift times on a ramp. An actual truck test shows that the anthropomorphic shifting strategy proposed in this study meets driver expectations and is conducive to the ramp driving of trucks with automated manual transmission.

An adaptive power distribution control strategy for an electric vehicle with dual-motor coupling in consideration of road gradient

An optimal power distribution control strategy is proposed in consideration of road gradient. Two original contributions are made to distinguish our work from current research. First, a sub-optimal State of Charge (SOC) predictive model is proposed based on Back Propagation (BP) neural network. The sampling set of the BP is obtained from the optimal results from Dynamic Programming (DP), based on a series of driving cycles in real-world and the corresponding road gradient. Second, an adaptive control method based on PID is proposed with the designed sub-optimal SOC predictive model. Specifically, the optimal shift schedule of the coupler is designed offline based on DP and is implemented into the controller in a prior fashion, to decouple the relationship between the coupler and the motors. Simulation results demonstrate that the proposed adaptive control strategy can realise optimally real-time power distribution control and is better than rule-based power distribution strategy.

An Integrated Approach for Shift Scheduling and Rostering Problems with Break Times for Inbound Call Centers

It may be very difficult to achieve the optimal shift schedule in call centers which have highly uncertain and peaked demand during short time periods. Overlapping shift systems are usually designed for such cases. This paper studies shift scheduling and rostering problems for inbound call centers where overlapping shift systems are used. An integer programming model that determines which shifts to be opened and how many operators to be assigned to these shifts is proposed for the shift scheduling problem. For the rostering problem both integer programming and constraint programming models are developed to determine assignments of operators to all shifts, weekly days-off, and meal and relief break times of the operators. The proposed models are tested on real data supplied by an outsource call center and optimal results are found in an acceptable computation time. An improvement of 15% in the objective function compared to the current situation is observed with the proposed model for the shift scheduling problem. The computational performances of the proposed integer and constraint programming models for the rostering problem are compared using real data observed at a call center and simulated test instances. In addition, benchmark instances are used to compare our Constraint Programming (CP) approach with the existing models. The results of the comprehensive computational study indicate that the constraint programming model runs more efficiently than the integer programming model for the rostering problem. The originality of this research can be attributed to two contributions: (a) a model for shift scheduling problem and two models for rostering problem are presented in detail and compared using real data and (b) the rostering problem is considered as a task-resource allocation and considerably shorter computation times are obtained by modeling this new problem via CP.