Conflicts between employee preferences and ergonomic recommendations in shift scheduling: regulation based on consent is not sufficient

OBJECTIVE: Contribution to the discussion of the role of participation/consent of employees in working hours regulation. METHODS: Exploratory analysis of conflicts between preferences of employees and ergonomic recommendations in shift scheduling by analysing a large number of participative shift scheduling projects. RESULTS: The analysis showed that very often the pursuit of higher income played the major role in the decision making process of employees and employees preferred working hours in conflict with health and safety principles. CONCLUSIONS: First, the consent of employees or the works council alone does not ensure ergonomically sound schedules. Besides consent, risk assessment procedures seem to be a promising but difficult approach. Secondly, more research is necessary to check the applicability of recommendations under various settings, to support the risk assessment processes and to improve regulatory approaches to working hours.

Shift Scheduling in Services When Employees Have Limited Availability: An L. P. Approach

This paper compares two linear programming (LP) models for shift scheduling in services where homogeneously-skilled employees are available at limited times. Although both models are based on set covering approaches, one explicitly matches employees to shifts, while the other imposes this matching implicitly. Each model is used in three forms—one with complete, another with very limited meal break placement flexibility, and a third without meal breaks—to provide initial schedules to a completion/improvement heuristic. The term completion/improvement heuristic is used to describe a construction/ improvement heuristic operating on a starting schedule. On 80 test problems varying widely in scheduling flexibility, employee staffing requirements, and employee availability characteristics, all six LP-based procedures generated lower cost schedules than a comparison from-scratch construction/improvement heuristic. This heuristic, which perpetually maintains an explicit matching of employees to shifts, consists of three phases which add, drop, and modify shifts. In terms of schedule cost, schedule generation time, and model size, the procedures based on the implicit model performed better, as a group, than those based on the explicit model. The LP model with complete break placement flexibility and implicitly matching employees to shifts generated schedules costing 6.7% less than those developed by the from-scratch heuristic.

Improved Implicit Optimal Modeling of the Labor Shift Scheduling Problem

This paper presents an integer programming model for developing optimal shift schedules while allowing extensive flexibility in terms of alternate shift starting times, shift lengths, and break placement. The model combines the work of Moondra (1976) and Bechtold and Jacobs (1990) by implicitly matching meal breaks to implicitly represented shifts. Moreover, the new model extends the work of these authors to enable the scheduling of overtime and the scheduling of rest breaks. We compare the new model to Bechtold and Jacobs' model over a diverse set of 588 test problems. The new model generates optimal solutions more rapidly, solves problems with more shift alternatives, and does not generate schedules violating the operative restrictions on break timing.

Labor Scheduling Using NPV Estimates of the Marginal Benefit of Additional Labor Capacity

An extensive literature exists on the problems of daily (shift) and weekly (tour) labor scheduling. In representing requirements for employees in these problems, researchers have used formulations based either on the model of Dantzig (1954) or on the model of Keith (1979). We show that both formulations have weakness in environments where management knows, or can attempt to identify, how different levels of customer service affect profits. These weaknesses results in lower-than-necessary profits. This paper presents a New Formulation of the daily and weekly Labor Scheduling Problems (NFLSP) designed to overcome the limitations of earlier models. NFLSP incorporates information on how changing the number of employees working in each planning period affects profits. NFLP uses this information during the development of the schedule to identify the number of employees who, ideally, should be working in each period. In an extensive simulation of 1,152 service environments, NFLSP outperformed the formulations of Dantzig (1954) and Keith (1979) at a level of significance of 0.001. Assuming year-round operations and an hourly wage, including benefits, of $6.00, NFLSP's schedules were $96,046 (2.2%) and $24,648 (0.6%) more profitable, on average, than schedules developed using the formulations of Danzig (1954) and Keith (1979), respectively. Although the average percentage gain over Keith's model was fairly small, it could be much larger in some real cases with different parameters. In 73 and 100 percent of the cases we simulated NFLSP yielded a higher profit than the models of Keith (1979) and Danzig (1954), respectively.

Optimisation des horaires des agents et du routage des appels dans les centres d’appels

Nous étudions la gestion de centres d'appels multi-compétences, ayant plusieurs types d'appels et groupes d'agents. Un centre d'appels est un système de files d'attente très complexe, où il faut généralement utiliser un simulateur pour évaluer ses performances. Tout d'abord, nous développons un simulateur de centres d'appels basé sur la simulation d'une chaîne de Markov en temps continu (CMTC), qui est plus rapide que la simulation conventionnelle par événements discrets. À l'aide d'une méthode d'uniformisation de la CMTC, le simulateur simule la chaîne de Markov en temps discret imbriquée de la CMTC. Nous proposons des stratégies pour utiliser efficacement ce simulateur dans l'optimisation de l'affectation des agents. En particulier, nous étudions l'utilisation des variables aléatoires communes. Deuxièmement, nous optimisons les horaires des agents sur plusieurs périodes en proposant un algorithme basé sur des coupes de sous-gradients et la simulation. Ce problème est généralement trop grand pour être optimisé par la programmation en nombres entiers. Alors, nous relaxons l'intégralité des variables et nous proposons des méthodes pour arrondir les solutions. Nous présentons une recherche locale pour améliorer la solution finale. Ensuite, nous étudions l'optimisation du routage des appels aux agents. Nous proposons une nouvelle politique de routage basé sur des poids, les temps d'attente des appels, et les temps d'inoccupation des agents ou le nombre d'agents libres. Nous développons un algorithme génétique modifié pour optimiser les paramètres de routage. Au lieu d'effectuer des mutations ou des croisements, cet algorithme optimise les paramètres des lois de probabilité qui génèrent la population de solutions. Par la suite, nous développons un algorithme d'affectation des agents basé sur l'agrégation, la théorie des files d'attente et la probabilité de délai. Cet algorithme heuristique est rapide, car il n'emploie pas la simulation. La contrainte sur le niveau de service est convertie en une contrainte sur la probabilité de délai. Par après, nous proposons une variante d'un modèle de CMTC basé sur le temps d'attente du client à la tête de la file. Et finalement, nous présentons une extension d'un algorithme de coupe pour l'optimisation stochastique avec recours de l'affectation des agents dans un centre d'appels multi-compétences.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

A heuristic algorithm based on multi-assignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust. © 2013 Springer Science+Business Media New York.

Integrating Crew Scheduling and Rostering Problems

Crew scheduling and crew rostering are similar and related problems which can be solved by similar procedures. So far, the existing solution methods usually create a model for each one of these problems (scheduling and rostering), and when they are solved together in some cases an interaction between models is considered in order to obtain a better solution. A single set covering model to solve simultaneously both problems is presented here, where the total quantity of drivers needed is directly considered and optimized. This integration allows to optimize all of the depots at the same time, while traditional approaches needed to work depot by depot, and also it allows to see and manage the relationship between scheduling and rostering, which was known in some degree but usually not easy to quantify as this model permits. Recent research in the area of crew scheduling and rostering has stated that one of the current challenges to be achieved is to determine a schedule where crew fatigue, which depends mainly on the quality of the rosters created, is reduced. In this approach rosters are constructed in such way that stable working hours are used in every week of work, and a change to a different shift is done only using free days in between to make easier the adaptation to the new working hours. Computational results for real-world-based instances are presented. Instances are geographically diverse to test the performance of the procedures and the model in different scenarios.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

An MILP-based heuristic for staff scheduling problems with acceptance levels

We present a real-world staff-assignment problem that was reported to us by a provider of an online workforce scheduling software. The problem consists of assigning employees to work shifts subject to a large variety of requirements related to work laws, work shift compatibility, workload balancing, and personal preferences of employees. A target value is given for each requirement, and all possible deviations from these values are associated with acceptance levels. The objective is to minimize the total number of deviations in ascending order of the acceptance levels. We present an exact lexicographic goal programming MILP formulation and an MILP-based heuristic. The heuristic consists of two phases: in the first phase a feasible schedule is built and in the second phase parts of the schedule are iteratively re-optimized by applying an exact MILP model. A major advantage of such MILP-based approaches is the flexibility to account for additional constraints or modified planning objectives, which is important as the requirements may vary depending on the company or planning period. The applicability of the heuristic is demonstrated for a test set derived from real-world data. Our computational results indicate that the heuristic is able to devise optimal solutions to non-trivial problem instances, and outperforms the exact lexicographic goal programming formulation on medium- and large-sized problem instances.

Adapting mode switches into the hierarchical scheduling

Mode switches are used to partition the system’s behavior into different modes to reduce the complexity of large embedded systems. Such systems operate in multiple modes in which each one corresponds to a specific application scenario; these are called Multi-Mode Systems (MMS). A different piece of software is normally executed for each mode. At any given time, the system can be in one of the predefined modes and then be switched to another as a result of a certain condition. A mode switch mechanism (or mode change protocol) is used to shift the system from one mode to another at run-time. In this thesis we have used a hierarchical scheduling framework to implement a multi-mode system called Multi-Mode Hierarchical Scheduling Framework (MMHSF). A two-level Hierarchical Scheduling Framework (HSF) has already been implemented in an open source real-time operating system, FreeRTOS, to support temporal isolation among real-time components. The main contribution of this thesis is the extension of the HSF featuring a multimode feature with an emphasis on making minimal changes in the underlying operating system (FreeRTOS) and its HSF implementation. Our implementation uses fixed-priority preemptive scheduling at both local and global scheduling levels and idling periodic servers. It also now supports different modes of the system which can be switched at run-time. Each subsystem and task exhibit different timing attributes according to mode, and upon a Mode Change Request (MCR) the task-set and timing interfaces of the entire system (including subsystems and tasks) undergo a change. A Mode Change Protocol specifies precisely how the system-mode will be changed. However, an application may not only need to change a mode but also a different mode change protocol semantic. For example, the mode change from normal to shutdown can allow all the tasks to be completed before the mode itself is changed, while changing a mode from normal to emergency may require aborting all tasks instantly. In our work, both the system mode and the mode change protocol can be changed at run-time. We have implemented three different mode change protocols to switch from one mode to another: the Suspend/resume protocol, the Abort protocol, and the Complete protocol. These protocols increase the flexibility of the system, allowing users to select the way they want to switch to a new mode. The implementation of MMHSF is tested and evaluated on an AVR-based 32 bit board EVK1100 with an AVR32UC3A0512 micro-controller. We have tested the behavior of each system mode and for each mode change protocol. We also provide the results for the performance measures of all mode change protocols in the thesis. RESUMEN Los conmutadores de modo son usados para particionar el comportamiento del sistema en diferentes modos, reduciendo así la complejidad de grandes sistemas empotrados. Estos sistemas tienen multiples modos de operación, cada uno de ellos correspondiente a distintos escenarios y para distintas aplicaciones; son llamados Sistemas Multimodales (o en inglés “Multi-Mode Systems” o MMS). Normalmente cada modo ejecuta una parte de código distinto. En un momento dado el sistema, que está en un modo concreto, puede ser cambiado a otro modo distinto como resultado de alguna condicion impuesta previamente. Los mecanismos de cambio de modo (o protocolos de cambio de modo) son usados para mover el sistema de un modo a otro durante el tiempo de ejecución. En este trabajo se ha usado un modelo de sistema operativo para implementar un sistema multimodo llamado MMHSF, siglas en inglés correspondientes a (Multi-Mode Hierarchical Scheduling Framework). Este sistema está basado en el HSF (Hierarchical Scheduling Framework), un modelo de sistema operativo con jerarquía de dos niveles, implementado en un sistema operativo en tiempo real de libre distribución llamado FreeRTOS, capaz de permitir el aislamiento temporal entre componentes. La principal contribución de este trabajo es la ampliación del HSF convirtiendolo en un sistema multimodo realizando los cambios mínimos necesarios sobre el sistema operativo FreeRTOS y la implementación ya existente del HSF. Esta implementación usa un sistema de planificación de prioridad fija para ambos niveles de jerarquía, ocupando el tiempo entre tareas con un “modo reposo”. Además el sistema es capaz de cambiar de un modo a otro en tiempo de ejecución. Cada subsistema y tarea son capaces de tener distintos atributos de tiempo (prioridad, periodo y tiempo de ejecución) en función del modo. Bajo una demanda de cambio de modo (Mode Change Request MCR) se puede variar el set de tareas en ejecución, así como los atributos de los servidores y las tareas. Un protocolo de cambio de modo espeficica precisamente cómo será cambiado el sistema de un modo a otro. Sin embargo una aplicación puede requerir no solo un cambio de modo, sino que lo haga de una forma especifica. Por ejemplo, el cambio de modo de “normal” a “apagado” puede permitir a las tareas en ejecución ser finalizadas antes de que se complete la transición, pero sin embargo el cambio de “normal” a “emergencia” puede requerir abortar todas las tareas instantaneamente. En este trabajo ambas características, tanto el modo como el protocolo de cambio, pueden ser cambiadas en tiempo de ejecución, pero deben ser previamente definidas por el desarrollador. Han sido definidos tres protocolos de cambios: el protocolo “suspender/continuar”, protocolo “abortar” y el protocolo “completar”. Estos protocolos incrementan la flexibilidad del sistema, permitiendo al usuario seleccionar de que forma quieren cambiar hacia el nuevo modo. La implementación del MMHSF ha sido testada y evaluada en una placa AVR EVK1100, con un micro-controlador AVR32UC3A0. Se ha comprobado el comportamiento de los distintos modos para los distintos protocolos, definidos previamente. Como resultado se proporcionan las medidades de rendimiento de los distintos protocolos de cambio de modo.

A Component Based Heuristic Search Method with AdaptivePerturbations for Hospital Personnel Scheduling

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with adaptive perturbations, for a nurse scheduling problem arising at a major UK hospital. The main idea behind this technique is to decompose a schedule into its components (i.e. the allocated shift pattern of each nurse), and then mimic a natural evolutionary process on these components to iteratively deliver better schedules. The worthiness of all components in the schedule has to be continuously demonstrated in order for them to remain there. This demonstration employs a dynamic evaluation function which evaluates how well each component contributes towards the final objective. Two perturbation steps are then applied: the first perturbation eliminates a number of components that are deemed not worthy to stay in the current schedule; the second perturbation may also throw out, with a low level of probability, some worthy components. The eliminated components are replenished with new ones using a set of constructive heuristics using local optimality criteria. Computational results using 52 data instances demonstrate the applicability of the proposed approach in solving real-world problems.

Effects of naps at work on the sleepiness of 12-hour night shift nursing personnel

Background and objective: The purpose of the present study was to evaluate the effects of a nap at work on the sleepiness of 12-hour, night-shift (registered and assistant) nursing personnel.Methods: Twelve nurses filled out daily logs, the Karolinska Sleepiness Scale (KS), and wore wrist actigraphs for two periods of four continuous days.Results: Mean nap duration during the night shifts was 138.3 (SD+39.8) minutes. The mean sleepiness level assessed by the KS score was lower, 3.3 (SD±1.6), when the nap was taken during the first span (00:01 - 03:00h) of the night shift, compared with 6.6 (SD±1.0) when there was no nap. The mean sleepiness level assessed by the KS score was also lower, 3.6 (SD±0.9), when the nap was taken during the second span (03:01 - 06:00h) of the night shift, compared with 7.0 (SD±1.1) when there was no nap. Thus, napping either during the first or second part of the night shift reduces sleepiness of 12-hour, night-shift nursing personnel. Moreover, the mean duration of the first sleep episode after night work was longer in those who did not nap than in those who did. Conclusions: The results of this study show that napping during the 12-hour, night-shift results in less sleepiness at work and less need for recovery sleep after work

Diffractive phase-shift lithography photomask operating in proximity printing mode

A phase shift proximity printing lithographic mask is designed, manufactured and tested. Its design is based on a Fresnel computer-generated hologram, employing the scalar diffraction theory. The obtained amplitude and phase distributions were mapped into discrete levels. In addition, a coding scheme using sub-cells structure was employed in order to increase the number of discrete levels, thus increasing the degree of freedom in the resulting mask. The mask is fabricated on a fused silica substrate and an amorphous hydrogenated carbon (a:C-H) thin film which act as amplitude modulation agent. The lithographic image is projected onto a resist coated silicon wafer, placed at a distance of 50 mu m behind the mask. The results show a improvement of the achieved resolution - linewidth as good as 1.5 mu m - what is impossible to obtain with traditional binary masks in proximity printing mode. Such achieved dimensions can be used in the fabrication of MEMS and MOEMS devices. These results are obtained with a UV laser but also with a small arc lamp light source exploring the partial coherence of this source. (C) 2010 Optical Society of America

A Paradigm Shift in Predoctoral Dental Curricula in Brazil: Evaluating the Process of Change

In 2002, the Brazilian Ministry of Education approved the official curricular guidelines for undergraduate courses in Brazil to be adopted by the nation's 188 dental schools. In 2005-06, the Brazilian Dental Education Association (BDEA) promoted workshops in forty-eight of the schools to verify the degree of transformation of the curriculum based on these guidelines. Among the areas analyzed were course philosophy (variables were v1: knowledge production based on the needs of the Brazilian Public Health System [BPHS]; v2: health determinants; and v3: postgraduate studies and permanent education); pedagogical skills (v4: curricular structure; v5: changes in pedagogic and didactic skills; and v6: course program orientation); and dental practice scenarios (v7: diversity of the scenarios for training/learning; v8: academic health care centers opened to the BPHS; and v9: participation of students in health care delivery for the population). The subjects consisted of faculty members (n=711), students (n=228), and employees (n=14). The results showed an incipient degree of curriculum transformation. The degree of innovation was statistically different depending on the type of university (public or private) for variables I, 2, 4, 5, 6, and 7. Private schools reported a higher level of innovation than public institutions. Resistance to transforming the dental curriculum according to the official guidelines may be linked to an ideological conception that supports the private practice model, continues to have faculty members direct all classroom activities, and prevents students from developing an understanding of professional practice as targeted towards the oral health needs of all segments of society.