Resource constrained routing and scheduling: Review and research prospects

In the service industry, it is crucial to efficiently allocate scarce resources to perform tasks and meet particular service requirements. What considerably complicates matters is when these resources, for example skilled technicians, nurses, and home carers have to visit different customer locations. This paper provides a comprehensive survey on resource constrained routing and scheduling that unveils the problem characteristics with respect to resource qualifications, service requirements and problem objectives. It also identifies the most effective exact and heuristic algorithms for this class of problems. The paper closes with several research prospects

Fairness aspects in personnel scheduling

In industries like health care, public transport or call centers a shift-based system ensures permanent availability of employees for covering needed services. The resource allocation problem – assigning employees to shifts – is known as personnel scheduling in literature and often aims at minimizing staffing costs. Working in shifts, though, impacts employees’ private lives which adds to the problem of increasing staff shortage in recent years. Therefore, more and more effort is spent on incorporating fairness into scheduling approaches in order to increase employees’ satisfaction. This paper presents a literature review of approaches for personnel scheduling considering fairness aspects. Since fairness is not a quantitative objective, but can be evaluated from different point of views, a large number of fairness measurements exists in the literature. Furthermore, perspective (group vs individual fairness) or time horizon (short-term vs long-term fairness) are often considered very differently. To conclude, we show that a uniform definition and approach for considering fairness in personnel scheduling is challenging and point out gaps for future research

Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

Patient and Nurse Considerations in Home Health Routing with Remote Monitoring Devices

We build on the current consistent vehicle routing problem literature by formulating a novel multi- objective mathematical model of the home health scheduling and routing problem that includes the option of assigning some patient visits to remote monitoring devices, with the objectives of mini- mizing total cost, achieving nurse consistency and creating balanced nurse workloads. A heuristic solution approach that approximates the efficient frontier of this multiobjective problem is pre- sented and validated, and the results of using this methodology to solve several realistic instances are included. We also analyze the assignment of patients to devices and present some managerial insights into making these assignments in practice

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