A survey on constructing rosters for air traffic controllers

In this survey the state-of-the-art technology and the literature to date are discussed. In particular, we will discuss the gap in the literature concerning rostering staff to tasks by qualifications, with the inclusion of restrictions on a measure of task familiarity, which is a unique consequence of the structure of ATC operations

Revisión de literatura sobre los modelos de optimización en programación de turnos de enfermería

Siendo la programación de turnos de enfermería (NSP) un componente esencial en la calidad del servicio de salud y debido al gran número de investigaciones desarrolladas sobre NSP en la literatura, se desarrolla una revisión de literatura sobre los artículos sobre NSP realizados desde 2003 hasta la fecha. A partir de este trabajo se logran identificar la tendencia y las necesidades propias de este problema, las cuales se caracterizan por (1) la necesidad de cerrar la brecha entre academia y práctica mediante el desarrollo de modelos objetivos de representación del problema y (2), desarrollar investigación sobre técnicas de solución capaces de tratar modelos de gran complejidad, sin sacrificar el recurso computacional. Este artículo presenta una revisión de literatura sobre los modelos de optimización en la programación de turnos de enfermería, publicados desde 2003 a la fecha.B Being the nurse shift scheduling an essential component of the quality of the health service and due to the big amount of research conducted regarding the Nurse Scheduling Problem (NSP), a literature review is carried out concerning articles on NSP published from 2003 up to now. As a result of this work, we were able to highlight the tendencies and own needs of this problem, which are characterized by: (1) the need to close the gap between academy and practice through the development of objective models that represent the problem and (2) research about solution techniques capable of processing models of great complexity, without sacrificing the computational resource. This article presents a literature review on optimization models in the NSP published since 2003

Applications of Mathematical Programming in Personnel Scheduling

In the few decades of its existence, mathematical programming has evolved into an important branch of operations research and management science. This thesis consists of four papers in which we apply mathematical programming to real-life personnel scheduling and project management problems. We develop exact mathematical programming formulations. Furthermore, we propose effective heuristic strategies to decompose the original problems into subproblems that can be solved effciently with tailored mathematical programming formulations. We opt for solution methods that are based on mathematical programming, because their advantages in practice are a) the exibility to easily accommodate changes in the problem setting, b) the possibility to evaluate the quality of the solutions obtained, and c) the possibility to use general-purpose solvers, which are often the only software available in practice

Bus driver rostering by hybrid methods based on column generation

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2018Rostering problems arise in a diversity of areas where, according to the business and labor rules, distinct variants of the problem are obtained with different constraints and objectives considered. The diversity of existing rostering problems, allied with their complexity, justifies the activity of the research community addressing them. The current research on rostering problems is mainly devoted to achieving near-optimal solutions since, most of the times, the time needed to obtain optimal solutions is very high. In this thesis, a Bus Driver Rostering Problem is addressed, to which an integer programming model is adapted from the literature, and a new decomposition model with three distinct subproblems representations is proposed. The main objective of this research is to develop and evaluate a new approach to obtain solutions to the problem in study. The new approach follows the concept of search based on column generation, which consists in using the column generation method to solve problems represented by decomposition models and, after, applying metaheuristics to search for the best combination of subproblem solutions that, when combined, result in a feasible integer solution to the complete problem. Besides the new decomposition models proposed for the Bus Driver Rostering Problem, this thesis proposes the extension of the concept of search by column generation to allow using population-based metaheuristics and presents the implementation of the first metaheuristic using populations, based on the extension, which is an evolutionary algorithm. There are two additional contributions of this thesis. The first is an heuristic allowing to obtain solutions for the subproblems in an individual or aggregated way and the second is a repair operator which can be used by the metaheuristics to repair infeasible solutions and, eventually, generate missing subproblem solutions needed. The thesis includes the description and results from an extensive set of computational tests. Multiple configurations of the column generation with three decomposition models are tested to assess the best configuration to use in the generation of the search space for the metaheuristic. Additional tests compare distinct single-solution metaheuristics and our basic evolutionary algorithm in the search for integer solutions in the search space obtained by the column generation. A final set of tests compares the results of our final algorithm (with the best column generation configuration and the evolutionary algorithm using the repair operator) and the solutions obtained by solving the problem represented by the integer programming model with a commercial solver.Programa de Apoio à Formação Avançada de Docentes do Ensino Superior Politécnico (PROTEC), SFRH/PROTEC/67405/201

An Integrated Framework for Staffing and Shift Scheduling in Hospitals

Over the years, one of the main concerns confronting hospital management is optimising the staffing and scheduling decisions. Consequences of inappropriate staffing can adversely impact on hospital performance, patient experience and staff satisfaction alike. A comprehensive review of literature (more than 1300 journal articles) is presented in a new taxonomy of three dimensions; problem contextualisation, solution approach, evaluation perspective and uncertainty. Utilising Operations Research methods, solutions can provide a positive contribution in underpinning staffing and scheduling decisions. However, there are still opportunities to integrate decision levels; incorporate practitioners view in solution architectures; consider staff behaviour impact, and offer comprehensive applied frameworks. Practitioners’ perspectives have been collated using an extensive exploratory study in Irish hospitals. A preliminary questionnaire has indicated the need of effective staffing and scheduling decisions before semi-structured interviews have taken place with twenty-five managers (fourteen Directors and eleven head nurses) across eleven major acute Irish hospitals (about 50% of healthcare service deliverers). Thematic analysis has produced five key themes; demand for care, staffing and scheduling issues, organisational aspects, management concern, and technology-enabled. In addition to other factors that can contribute to the problem such as coordination, environment complexity, understaffing, variability and lack of decision support. A multi-method approach including data analytics, modelling and simulation, machine learning, and optimisation has been employed in order to deliver adequate staffing and shift scheduling framework. A comprehensive portfolio of critical factors regarding patients, staff and hospitals are included in the decision. The framework was piloted in the Emergency Department of one of the leading and busiest university hospitals in Dublin (Tallaght Hospital). Solutions resulted from the framework (i.e. new shifts, staff workload balance, increased demands) have showed significant improvement in all key performance measures (e.g. patient waiting time, staff utilisation). Management team of the hospital endorsed the solution framework and are currently discussing enablers to implement the recommendation

Selection hyper-heuristics for healthcare scheduling

A variety of approaches have been used to solve a variety of combinatorial optimisation problems. Many of those approaches are tailored to the particular problem being addressed. Recently, there has been a growing number of studies towards providing more general search methodologies than currently exist which are applicable to different problem domains without requiring any algorithmic modification. Hyper-heuristics represent a class of such general methodologies which are capable of automating the design of search process via generating new heuristics and/or mixing existing heuristics to solve hard computational problems. This study focuses on the design of selection hyper-heuristics which attempt to improve an initially created solution iteratively through heuristic selection and move acceptance processes and their application to the real-world healthcare scheduling problems, particularly, nurse rostering and surgery admission planning. One of the top previously proposed general hyper-heuristic methodology was an adaptive hyper-heuristic consisting of many parameters, although their values were either fixed or set during the search process, with a complicated design. This approach ranked the first at an international cross-domain heuristic search challenge among twenty other competitors for solving instances from six different problem domains, including maximum satisfiability, one dimensional bin packing, permutation flow shop, personnel scheduling, travelling salesman, vehicle routing problems. The hyper-heuristics submitted to the competition along with the problem domain implementations can now be considered as the benchmark for hyper-heuristics. This thesis describes two new easy-to-implement selection hyper-heuristics and their variants based on iterated and greedy search strategies. A crucial feature of the proposed hyper-heuristics is that they necessitate setting of less number of parameters when compared to many of the existing approaches. This entails an easier and more efficient implementation, since less time and effort is required for parameter tuning. The empirical results show that our most efficient and effective hyper-heuristic which contains only a single parameter outperforms the top ranking algorithm from the challenge when evaluated across all six problem domains. Moreover, experiments using additional nurse rostering problems which are different than the ones used in the challenge and surgery scheduling problems show that the results found by the proposed hyper-heuristics are very competitive, yielding with the best known solutions in some cases

Modelling and evaluation issues in nurse rostering

In practice nurse rostering problems are often too complex to be expressed through available academic models. Such models are not rich enough to represent the variegated nature of real world scenarios, and therefore have no practical relevance. This article focuses on two particular modelling issues that require careful consideration in making academic nurse rostering approaches re-usable in a real world environment. First: introducing several complex problem characteristics, resulting in a rich, generic model. A detailed description is provided for researchers interested in using this new model. We also present a novel benchmark dataset based on this rich model. Second: the consideration of a consistent evaluation procedure that corresponds to realistic quality measurement. These contributions will enable faster implementation of academic nurse rostering achievements in real hospital environments. A suite of hyper-heuristics is presented. These are capable of solving these rich personnel rostering problems using the presented evaluation procedures. Their performance is compared to that of another meta-heuristic.status: publishe