Advanced Methods and Models for Employee Timetabling Problems

This thesis is focused on the design of efficient models and algorithms for employee timetabling problems (ETPs). From our point of view, there are two significant gaps in the current state of the art. The first one, also important in practice, concerns the ETP with strongly varying workforce demand. Unlike the classical Nurse Rostering Problem (NRP) this problem considers dozens of shift types that can cover the demand more precisely than early, late and night shift type used in NRP. In this work we call this problem the Employee Timetabling Problem with a High Diversity of shifts (ETPHD). It comes as no surprise that the exact methods like Integer Linear Programming are not able to find its solution in reasonable time. Therefore, a transformation of ETPHD based on mapping of shift types to shift kinds was proposed. The transformation allows one to design a multistage approach (MSA). The aim of the first two stages is to find an initial ETPHD solution, where a rough position of assigned shifts is determined. This proved to be substantial for the last stage of MSA, where the solution is consequently improved in terms of its quality. In order to verify the MSA performance, a cross evaluation methodology was proposed. It is based on the comparison of the performance provided by more approaches on more combinatorial problems. Therefore, real life ETPHD instances from an airport ground company and also standard benchmark NRP instances were considered. The experiments confirmed the better or equal performance of our approach in the most of the cases. The second gap in the literature is an absence of parallel algorithms for ETPs. We focused on the Nurse Rerostering Problem (NRRP) that appears when a disruption in the roster occurs, e.g., when one of the employees becomes sick. For this purpose, the parallel algorithm solving NRRP was proposed in order to shorten needed computational time. This algorithm was designed for a Graphics Processing Unit (GPU) offering a massive parallelization. To the best of our knowledge, this is the first usage of GPU for ETPs. The performance of the GPU parallel algorithm was tested on the real life NRRP benchmark instances and evaluated from two points of view. Firstly, the quality of the results was compared to the known results from the state of the art. Secondly, the speedup achieved by the parallel algorithm related to the sequential one was verified. In average, the parallel algorithm is able to provide the results of the same quality 15 times faster than the sequential one.Katedra řídicí technik

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

A study of evoluntionary perturbative hyper-heuristics for the nurse rostering problem.

Master of Science in Computer Science. University of KwaZulu-Natal, Pietermaritzburg 2017.Hyper-heuristics are an emerging field of study for combinatorial optimization. The aim of a hyper-heuristic is to produce good results across a set of problems rather than producing the best results. There has been little investigation of hyper-heuristics for the nurse rostering problem. The majority of hyper-heuristics for the nurse rostering problem fit into a single type of hyper-heuristic, the selection perturbative hyper-heuristic. There is no work in using evolutionary algorithms employed as selection perturbative hyper-heuristics for the nurse rostering problem. There is also no work in using the generative perturbative type of hyper-heuristic for the nurse rostering problem. The first objective of this dissertation is to investigate the selection perturbative hyper-heuristic for the nurse rostering problem and the effectiveness of employing an evolutionary algorithm (SPHH). The second objective is to investigate a generative perturbative hyper-heuristic to evolve perturbation heuristics for the nurse rostering problem using genetic programming (GPHH). The third objective is to compare the performance of SPHH and GPHH. SPHH and GPHH were evaluated using the INRC2010 benchmark data set and the results obtained were compared to available results from literature. The INRC2010 benchmark set is comprised of sprint, medium and long instance types. SPHH and GPHH produced good results for the INRC2010 benchmark data set. GPHH and SPHH were found to have different strengths and weaknesses. SPHH found better results than GPHH for the medium instances. GPHH found better results than SPHH for the long instances. SPHH produced better average results. GPHH produced results that were closer to the best known results. These results suggest future research should investigate combining SPHH and GPHH to benefit from the strengths of both perturbative hyper-heuristics

Resource management in pre-vocational education: A study of TVEI in two LEAs.

The study addresses the management of pre-vocational education programmes in secondary education with particular reference to the management of resources. The educational context is the Technical and Vocational Education Initiative (TVEI) in the United Kingdom which provides opportunities for curriculum and management innovations through experimentation at the local level. The research broadly explores the roles and relationships between the central government, local education authorities (LEAs) and institutions in the delivery of a directly funded educational programme. The primary focus, however, is on determining and interpreting resource allocation forces and the rationale for allocations in secondary schools. A review of literature on the TVEI, educational innovations and the management of resources leads to a conceptual framework which conceives school activities as comprising 'programmes', with each programme representing a coherent set of resourced activities with its own objectives. A review of literature on the rational and political perspectives on management provides the basis on which the allocative choices of selected schools are interpreted. The research methodology draws from both positivist and interpretative approaches. It consists of a case study method, involving two LEAs and four schools (two in each LEA), using documentation and interview as the major research instruments. Using the concept of full-time (pupils and teachers) equivalence as basis, the allocative choices of the schools are assessed against four performance measures - the impact of subjects and the TVEI, economy in the use of resources, equity/ba1ance in the allocation of resources, and pressure/1oad on teachers. The analysis leads to the conclusion that the relative distribution of resources to subjects and other school activities will necessarily vary because school objectives are not only many and varied, but also make different resource demands. However, it was also found that, in resource terms, some objectives appeared to be in conflict with others, suggesting that specific educational and resource objectives not only need to be specified, but also considered together when making allocative choices

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order