"You have to get wet to learn how to swim" applied to bridging the gap between research into personnel scheduling and its implementation in practice

Personnel scheduling problems have attracted research interests for several decades. They have been considerably changed over time, accommodating a variety of constraints related to legal and organisation requirements, part-time staff, flexible hours of staff, staff preferences, etc. This led to a myriad of approaches developed for solving personnel scheduling problems including optimisation, meta-heuristics, artificial intelligence, decision-support, and also hybrids of these approaches. However, this still does not imply that this research has a large impact on practice and that state-of-the art models and algorithms are widely in use in organisations. One can find a reasonably large number of software packages that aim to assist in personnel scheduling. A classification of this software based on its purpose will be proposed, accompanied with a discussion about the level of support that this software offers to schedulers. A general conclusion is that the available software, with some exceptions, does not benefit from the wealth of developed models and methods. The remaining of the paper will provide insights into some characteristics of real-world scheduling problems that, in the author’s opinion, have not been given a due attention in the personnel scheduling research community yet and which could contribute to the enhancement of the implementation of research results in practice. Concluding remarks are that in order to bridge the gap that still exists between research into personnel scheduling and practice, we need to engage more with schedulers in practice and also with software developers; one may say we need to get wet if we want to learn how to swim

Application of Quantum Annealing to Nurse Scheduling Problem

Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice. We investigate the empirical performance of quantum annealing to solve the Nurse Scheduling Problem (NSP) with hard constraints using the D-Wave 2000Q quantum annealing device. NSP seeks the optimal assignment for a set of nurses to shifts under an accompanying set of constraints on schedule and personnel. After reducing NSP to a novel Ising-type Hamiltonian, we evaluate the solution quality obtained from the D-Wave 2000Q against the constraint requirements as well as the diversity of solutions. For the test problems explored here, our results indicate that quantum annealing recovers satisfying solutions for NSP and suggests the heuristic method is sufficient for practical use. Moreover, we observe that solution quality can be greatly improved through the use of reverse annealing, in which it is possible to refine a returned results by using the annealing process a second time. We compare the performance NSP using both forward and reverse annealing methods and describe how these approach might be used in practice.Comment: 20 pages, 13 figure

Productivity and Skills in Industry and Services-A Britian-German Comparison

It is widely accepted that the vocational and professional training system has a major impact on national competitiveness. In this paper a number of German-British studies in manufacturing and services are examined in order to show how skill systems have affected the comparative strengths and weaknesses of the two countries’ productivity performances. The studies have been conducted since the end of the 1980s to 2003 and have revealed specific links between vocational training, products and competitiveness on the basis of matched plant comparisons. The comparison between Britain and Germany has been chosen as these countries have very different national VET systems. The findings suggest that higher levels of apprenticeship training in German companies give them an advantage over their British counterparts with respect to flexibility to changes in markets, technology, quality and supply chains. The paper closes with a short discussion.

Shift Work and the United States Female Workforce: The Relationship Between Shift Work and Ill-Health Effects

The present study was designed to determine the magnitude of the relationship between amount, frequency, and length of shift work completed by female transportation employees and the number, degree, and extent of problems related to physical, menstrual and psychological health including depression. It was hypothesized that workers that are employed in areas such as transportation who are working shift work on a regular basis place themselves at higher risk for developing health or psychosocial related effects. These health related outcomes can have a profound impact on an employee’s job performance, daily functioning, and personal life. The present study sought to understand the potential relationship between working shift work and higher disturbances to the bodies’ natural functioning. The present study has the potential for explaining new ways to decrease the risk factors for those working shift work by contributing to the overall understanding of this multifaceted relationship. This study has many important findings and implications. This study has implications for explaining that the effects of disturbances to the circadian rhythm as a result of certain shift work schedules can result in ill-related health effects. Additionally, this study sought to challenge limitations to current research that has been conducted on the topic as the majority of studies have been performed on men. The overall purpose of the study was to gain a better understanding of the negative effects of shift work on females working within the transportation industry. This study sought to explain the health implications specifically for female workers as fewer studies have been conducted with gender as a main effect in the analysis. The present study suggests that due to the circadian rhythm controlling hormone secretion within the body, disturbances to its natural rhythm can have additional effects on female cycles such as menstruation. Overall, this study offers implications for further research on females working shift work and highlights the continued importance for further exploration into recent developments. These implications have the potential to further our current understanding of the relationship between shift work and ill-health effects, particularly the factors that women face

Heuristic Algorithm for Workforce Scheduling Problems

In this paper we present a heuristic approach for solving workforce scheduling problems. The primary goal is to minimize the number of required workers given a pre-established shift demand over a planning horizon. The proposed algorithm starts with an initial solution (initial number of workers and their shift assignment) and iteratively searches the state space, moving towards better solutions via a local search procedure. Local optima are avoided by guaranteeing that the algorithm never returns to a previously visited solution. The algorithm stops after a termination criterion is met. The solution provides a detailed schedule of each worker on each shift. A number of constraints such as minimum and maximum number of working hours, rest days, and maximum number of continuous working hours are considered. The algorithm was tested on a number of randomly generated problems of different sizes. A Mixed Integer Programming (MIP) formulation is proposed and used as a benchmark. Computational experiments show that the algorithm always found optimal or near-optimal solutions with signifi cantly less computer effort

New Solution Approaches for Scheduling Problems in Production and Logistics

The current cumulative PhD thesis consists of six papers published in/submitted to scientific journals. The focus of the thesis is to develop new solution approaches for scheduling problems encountering in manufacturing as well as in logistics. The thesis is divided into two parts: “ma-chine scheduling in production” and “scheduling problems in logistics” each of them consisting three papers. To have most comprehensive overview of the topic of machine scheduling, the first part of the thesis starts with two systematic review papers, which were conducted on tertiary level (i.e., re-viewing literature reviews). Both of these papers analyze a sample of around 130 literature re-views on machine scheduling problems. The first paper use a subjective quantitative approach to evaluate the sample, while the second papers uses content analysis which is an objective quanti-tative approach to extract meaningful information from massive data. Based on the analysis, main attributes of scheduling problems in production are identified and are classified into sever-al categories. Although the focus of both these papers are set to review scheduling problems in manufacturing, the results are not restricted to machine scheduling problem and the results can be extended to the second part of the thesis. General drawbacks of literature reviews are identi-fied and several suggestions for future researches are also provided in both papers. The third paper in the first part of the thesis presents the results of 105 new heuristic algorithms developed to minimize total flow time of a set of jobs in a flowshop manufacturing environ-ment. The computational experiments confirm that the best heuristic proposed in this paper im-proves the average error of best existing algorithm by around 25 percent. The first paper in second part is focused on minimizing number of electric tow-trains responsi-ble to deliver spare parts from warehouse to the production lines. Together with minimizing number of these electric vehicles the paper is also focused to maximize the work load balance among the drivers of the vehicles. For this problem, after analyzing the complexity of the prob-lem, an opening heuristic, a mixed integer linear programing (MILP) model and a taboo-search neighborhood search approach are proposed. Several managerial insights, such as the effect of battery capacity on the number of required vehicles, are also discussed. The second paper of the second part addresses the problem of preparing unit loaded devices (ULDs) at air cargos to be loaded latter on in planes. The objective of this problem is to mini-mize number of workers required in a way that all existing flight departure times are met and number of available places for building ULDs is not violated. For this problem, first, a MILP model is proposed and then it is boosted with a couple of heuristics which enabled the model to find near optimum solutions in a matter of 10 seconds. The paper also investigates the inherent tradeoff between labor and space utilization as well as the uncertainty about the volume of cargo to be processed. The last paper of the second part proposes an integrated model to improve both ergonomic and economic performance of manual order picking process by rotating pallets in the warehouse. For the problem under consideration in this paper, we first present and MILP model and then pro-pose a neighborhood search based on simulated annealing. The results of numerical experiment indicate that selectively rotating pallets may reduce both order picking time as well as the load on order picker, which leads to a quicker and less risky order picking process

Fatigue and Sleep Quality Among Staff Nurses Working in A Tertiary Care Hospital During COVID-19 Pandemic

Introduction: Fatigue, a universal phenomenon, is a suboptimal psychophysiological condition caused by physical and/or mental exertion. Insufficient recovery between work shifts causes accumulated acute fatigue to progress into chronic. As fatigue and sleep quality are related, adequate sleep and inter shift recovery are thus vital to the overall health. The current COVID-19 pandemic has caused added burden to the nursing workforce worldwide. This study aimed to assess fatigue and sleep quality among staff nurses of a tertiary care hospital during the pandemic. Methods: A descriptive cross-sectional study was conducted among 151 staff nurses of Lumbini Medical College and Teaching Hospital (LMCTH) using enumerative sampling method. Valid and reliable instruments i.e., Occupational Fatigue Exhaustion Recovery (OFER) and Pittsburgh Sleep Quality Index (PSQI) were used. Analysis was done using descriptive and inferential statistics. Results: The mean ±SD age of the participants was 26.54±6.93 years. Less than half (39.1%) of them had moderate to high acute fatigue. Nearly half (41.2%) had high chronic fatigue and most (61.6%) had low to moderate inter shift recovery. Poor sleep was found among 60.9% of the participants with mean global PSQI score of 6.74. Sleep quality had moderate positive correlation with chronic (r=0.4, p<0.001) and acute (r=0.39, p<0.001) fatigue whereas had moderate negative correlation with inter shift recovery (r=- 0.41, p<0.001) which were statistically significant. Conclusion: The staff nurses had fatigue and poor sleep during COVID-19 pandemic. Nursing administration should take appropriate measures timely to decrease fatigue and improve sleep to prevent serious consequences