Reordering all agents in asynchronous backtracking for distributed constraint satisfaction problems

Distributed constraint satisfaction problems (DisCSPs) can express decision problems where physically distributed agents control different decision variables, but must coordinate with each other to agree on a global solution. Asynchronous Backtracking (ABT) is a pivotal search procedure for DisCSPs. ABT requires a static total ordering on the agents. However, reordering agents during search is an essential component for efficiently solving a DisCSP. All polynomial space algorithms proposed so far to improve ABT by reordering agents during search only allow a limited amount of reordering. In this paper, we propose AgileABT, a general framework for reordering agents asynchronously that is able to change the ordering of all agents. This is done via the original notion of termination value, a label attached to the orders exchanged by agents during search. We prove that AgileABT is sound and complete. We show that, thanks to termination values, our framework allows us to implement the main variable ordering heuristics from centralized CSPs, which until now could not be applied to the distributed setting. We prove that AgileABT terminates and has a polynomial space complexity in all these cases. Our empirical study shows the significance of our framework compared to state-of-the-art asynchronous dynamic ordering algorithms for solving distributed CSP

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

Integrationsaspekte der Simulation: Technik, Orgnisation und Personal, Karlsruhe, 7. und 8. Oktober 2010 = Integration Aspects of Simulation: Equipment, Organization and Personnell, Karlsruhe, 7th and 8th October 2010

Die Integration technischer, organisatorischer und personalorientierter Aspekte in Simulationsverfahren ist das Leitthema der 14. Fachtagung der Arbeitsgemeinschaft Simulation (ASIM) innerhalb der Gesellschaft für Informatik, die vom Institut für Arbeitswissenschaft und Betriebsorganisation im Oktober 2010 ausgerichtet wurde. Der vorliegende Tagungsband gibt somit einen vertiefenden Einblick in neue Entwicklungen und Beispiele guter Praxis der Simulation über den deutschsprachigen Raum hinaus

Hochflexibles Workforce Management

It can be observed that companies tend to use a very demand driven personnel scheduling instead of using fixed shifts. In this context the term highly flexible workforce management (WFM) is used. With instruments such as the planning of subdaily workplace rotations, the combination of working time model generation and personnel scheduling or the combination of personnel scheduling and vehicle routing the demand for personnel can be covered very well. Such problems are novel and found little attention by researchers up to now.In this work classical OR-algorithms, metaheuristics and multi-agent systems (MAS) are evaluated on real world problems from logistics, retail and British Telecom. It can be shown, that classical OR-algorithms are not appropriate for these problems of highly flexible WFM, because of impractical CPU-times. On the other hand selected metaheuristics are very suitable. MAS should not be favoured, because selected metaheuristics performed always better. It must point out that a hybrid algorithm (a metaheuristic with a problem-specific repair) is responsible for the success of metaheuristics. MAS lack of a central planning instance that makes major changes for which agents are not able to do. Numerous algorithms of this work where originally developed for continuous problems. The adaption to combinatorial problems is described too. The appropriate adaption of parameters is also addressed.Zunehmend ist bei Unternehmen ein Trend weg von der starren Schicht- oder Dienstplanung hin zu einer auf den Personalbedarf ausgerichteten Planung festzustellen. In diesem Zusammenhang wird der Begriff hochflexibles Workforce Management (WFM) geprägt. Mit Instrumenten wie der Planung untertägiger Arbeitsplatzwechsel, der Kombination aus Arbeitszeitmodellerstellung und Einsatzplanung sowie der kombinierten Personaleinsatz- und Tourenplanung kann der Personaleinsatz sehr gut an den Personalbedarf angepasst werden. Derartige Problemstellungen sind neuartig und fanden in der Forschung bisher wenig Beachtung