"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

Workforce scheduling and routing problems: literature survey and computational study

In the context of workforce scheduling, there are many scenarios in which personnel must carry out tasks at different locations hence requiring some form of transportation. Examples of these type of scenarios include nurses visiting patients at home, technicians carrying out repairs at customers’ locations and security guards performing rounds at different premises, etc. We refer to these scenarios as workforce scheduling and routing problems (WSRP) as they usually involve the scheduling of personnel combined with some form of routing in order to ensure that employees arrive on time at the locations where tasks need to be performed. The first part of this paper presents a survey which attempts to identify the common features of WSRP scenarios and the solution methods applied when tackling these problems. The second part of the paper presents a study on the computational difficulty of solving these type of problems. For this, five data sets are gathered from the literature and some adaptations are made in order to incorporate the key features that our survey identifies as commonly arising in WSRP scenarios. The computational study provides an insight into the structure of the adapted test instances, an insight into the effect that problem features have when solving the instances using mathematical programming, and some benchmark computation times using the Gurobi solver running on a standard personal computer

Modelling home care organisations from an operations management perspective

Home Care (HC) service consists of providing care to patients in their homes. During the last decade, the HC service industry experienced significant growth in many European countries. This growth stems from several factors, such as governmental pressure to reduce healthcare costs, demographic changes related to population ageing, social changes, an increase in the number of patients that suffer from chronic illnesses, and the development of new home-based services and technologies. This study proposes a framework that will enable HC service providers to better understand HC operations and their management. The study identifies the main processes and decisions that relate to the field of HC operations management. Hence, an IDEF0 (Integrated Definition for Function Modelling) activity-based model describes the most relevant clinical, logistical and organisational processes associated with HC operations. A hierarchical framework for operations management decisions is also proposed. This analysis is derived from data that was collected by nine HC service providers, which are located in France and Italy, and focuses on the manner in which operations are run, as well as associated constraints, inputs and outputs. The most challenging research areas in the field of HC operations management are also discussed

Management errors in adults with congenital heart disease: prevalence, sources, and consequences

AIMS: Improved survival has resulted in increasing numbers and complexity of adults with congenital heart disease (ACHD). International guidelines recommend specialized care but many patients are still not managed at dedicated ACHD centres. This study analysed referral sources and appropriateness of management for patients referred to our tertiary ACHD Centre over the past 3 years. METHODS AND RESULTS: We compared differences in care between patients referred from paediatric/ACHD-trained vs. general adult cardiologists, according to Adherence (A) or Non-Adherence (NA) with published guidelines. Non-Adherent cases were graded according to the severity of adverse outcome or risk of adverse outcome. Of 309 consecutively referred patients (28 ± 14 years, 51% male), 134 (43%) were from general cardiologists (19% highly complex CHD) and 115 (37%) were from paediatric cardiology or ACHD specialists (33% highly complex CHD). Sixty referrals (20%) were from other medical teams and of those, 31 had been lost to follow-up. Guideline deviations were more common in referrals from general compared to CHD-trained cardiologists (P < 0.001). Of general cardiology referrals, 49 (37%) were NA; 18 had catastrophic or major complications (n = 2, 16 respectively). In contrast, only 12 (10%) of the paediatric/ACHD referrals were NA, but none of these were catastrophic and only 3 were major. Simple, moderate, and highly complex CHD patients were at increased risk of adverse outcome when not under specialized CHD cardiology care (P = 0.04, 0.009, and 0.002, respectively). CONCLUSION: Non-adherence with guidelines was common in the ACHD population, and this frequently resulted in important adverse clinical consequences. These problems were more likely in patients who had not been receiving specialized CHD care. Configuring healthcare systems to optimize ‘whole of life’ care for this growing population is essential

An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints

This paper presents an investigation into the application of heuristic decomposition and mixed-integer programming to tackle workforce scheduling and routing problems (WSRP) that involve timedependent activities constraints. These constraints refer to time-wise dependencies between activities. The decomposition method investigated here is called repeated decomposition with con ict repair (RDCR) and it consists of repeatedly applying a phase of problem decomposition and sub-problem solving, followed by a phase dedicated to con ict repair. In order to deal with the time-dependent activities constraints, the problem decomposition puts all activities associated to the same location and their dependent activities in the same sub-problem. This is to guarantee the satisfaction of time-dependent activities constraints as each sub-problem is solved exactly with an exact solver. Once the assignments are made, the time windows of dependent activities are fixed even if those activities are subject to the repair phase. The paper presents an experimental study to assess the performance of the decomposition method when compared to a tailored greedy heuristic. Results show that the proposed RDCR is an effective approach to harness the power of mixed integer programming solvers to tackle the diffcult and highly constrained WSRP in practical computational time. Also, an analysis is conducted in order to understand how the performance of the different solution methods (the decomposition, the tailored heuristic and the MIP solver) is accected by the size of the problem instances and other features of the problem. The paper concludes by making some recommendations on the type of method that could be more suitable for different problem sizes