Multi-skilled Staff Research Articles

A multi-skilled staff scheduling and team configuration optimisation model for artificial intelligence project portfolio considering competence development and innovation-driven

This paper emphasises the pivotal role of enhancing research and development (R&D) staff competence and boosting team innovation efficiency in configuring R&D project teams for artificial intelligence (AI) product development. Diverging from traditional studies primarily focused on time, quality, and cost objectives, this study proposes prioritising the skill increments of staff and team diversity, aligning with the overarching goals of the R&D cycle. Targeting multi-skilled R&D personnel for scheduling and configuration, a three-objective tradeoff optimisation model is established. The nonlinear mixed-integer constrained programming model incorporates a learning effect for calculating employee skill value and employs a heterogeneity efficiency formula for assessing team diversity, particularly emphasising the diversity of R&D personnel research backgrounds. An algorithm based on Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is designed to obtain the approximate Pareto optimal solution. Furthermore, it compares the algorithm with the multi-objective particle swarm optimisation (MOPSO), explores practical decision-making methods for Pareto solutions, and conducts sensitivity analyses on the learning rate and diversity level. Our research is relevant to enterprises seeking to enhance R&D capabilities with a certain degree of homogeneity among R&D employees. This paper exemplifies and validates the proposed model and solution approach using a new AI product from a healthcare company.

The Multi-Skilled Resource-Constrained Project Scheduling Problem: A Systematic Review and an Exploration of Future Landscapes

Abstract The Multi-skilled Resource Constrained Project Scheduling Problem (MS-RCPSP) is a complex and multi-faceted problem that involves scheduling activities whilst considering various resource constraints. These constraints include limited availability of workers, equipment, and materials, with each activity requiring a minimal set of skills to be executed. Furthermore, for a better resemblance to reality, workers/machines are assumed to be multi-skilled/multi-purpose posing another dimension of complexity to the problem. The objective is to minimize project duration, cost, or other relevant criteria while accounting for the inherent resources flexibility. This paper provides a systematic review of the literature pertaining to MS-RCPSP, and an in-depth analysis of 171 papers published between 2000 and 2021 inclusive. The conducted bibliometric analysis identifies the top contributing authors, most influential papers, existing research tendencies, and thematic research topics within the field. In addition, this review highlights different aspects of the MS-RCPSP, spanning the significance of performance measures, solution approaches, application areas, and the incorporation of time constraints. While project completion time, cost, and tardiness are common performance indicators, other measures such as multi-skilled staff assignment and schedule robustness are also deemed important. Although various methods have been employed to solve the MS-RCPSP including exact and approximate approaches, the selection of the most-suited approach depends on the problem’s scale, complexity, and constraints, necessitating careful consideration of each method’s strengths and weaknesses. Interestingly, several studies have jointly addressed resource and time constraints in the context of MS-RCPSP, often considering tardiness, and have proposed different algorithms, models, and metaheuristics to tackle these challenges. This paper clearly highlights research gaps and promising avenues for future research. This work provides valuable insights for project managers to effectively schedule tasks in the presence of multiple flexible resources.

A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

A Two-Layer Approach for the Decentralized Multi-Project Scheduling Problem Sharing Multi-Skilled Staff

The Integrated Problem of Construction Project Scheduling and Multiskilled Staff Assignment with Learning Effect

Effective multiskill resource scheduling requires comprehensive workforce assignments. Drawing on the multiskill project scheduling problem perspective, this study investigates the integrated problem of project scheduling and multiskilled staffing based on a more realistic perspective that human skill level is dynamic and has a variable activity duration caused by the learning effect. An integer linear programming model is innovatively constructed to solve the problem directly. Moreover, an adapted tabu search algorithm with six resource-oriented priority strategies is designed to solve large-scale problems efficiently. Based on a realistic construction project case and numerical instances, comprehensive computational experiments are conducted to validate the proposed algorithm. The findings reveal the impact of different resource strategies on project duration and personal skill growth, particularly through the optimization of project scheduling according to the dynamic scenarios. The research extends conventional project scheduling knowledge and its methods by solving complex scheduling problems for improved project objectives and employee value. In practice, the model and the algorithm can be integrated into the project management information system for strategizing a plan of project scheduling and staff assignment proactively.

Proactive Operations Management: Staff Allocation with Competence Maintenance Constraints

Highly qualified staff are the key to successful operations management in any organization. In this paper, the emphasis is put on the problem of planning the rotational assignment of work tasks to a multi-skilled staff to guarantee maintaining their competencies at the required level. The aim of this study is to propose a novel declarative model for proactive planning of staff allocation whilst taking into account the forgetting effect. Sufficient conditions are proposed that allow for the cyclical rotation of employees between different tasks in order to keep their competencies at a constant level. The numerical experiments prove that the presented approach allows for finding a trade-off between a robustness to absenteeism and maintaining staff competency levels. The proposed method is suitable for human resource-related decision making in an interactive mode.

A Two-Stage Algorithm Based on 12 Priority Rules for the Stochastic Distributed Resource-Constrained Multi-Project Scheduling Problem With Multi-Skilled Staff

In practical multi-skilled resource-constrained multi-project management, the activity duration is often affected by some factors (e.g., rework, increased workload), leading to uncertainty. Moreover, multiple projects are often managed under a distributed decision-making environment. To deal with uncertain activity durations in distributed multi-project management with multi-skilled staff, this paper studies a stochastic distributed resource-constrained multi-project scheduling problem with multi-skilled staff (MS-SDRCMPSP). In a distributed decision-making environment, a two-stage model with local scheduling and global coordination stages is established to describe MS-SDRCMPSP. A two-stage algorithm with 12 priority rules (TSA-12PRs) is proposed, these 12 priority rules are composed of 4 activity priority rules and 3 resource priority rules. In the local schedule stage, 4 activity priority rules (PRs) are applied to obtain the local schedule plan. In the global coordination phase, we develop 3 resource PRs based on variable neighborhood search (VNS), of which VNS is used to solve the execution order of conflicting projects, and 3 resource PRs are developed to formulate multi-skilled resource assignment strategies. Based on the multi-skilled instances adapted from benchmark instances, we evaluate the performance of the 12 PRs on different instances. The experiment results show that two PRs among 12 PRs perform better than other PRs in all-size instances. Comparing the two-stage algorithm with better two PRs with other approaches in literatures, we find that our method performs better than other approaches, especially in large-size instances. In addition, further experiments show that our method is more conducive to shortening the CPU runtime on distributed problems than centralized methods.

A two-stage approach with softmax scoring mechanism for a multi-project scheduling problem sharing multi-skilled staff

This paper studies a multi-project scheduling problem sharing multi-skilled staff (MSMPSP). In a distributed decision-making environment, each project is independently scheduled by its project managers, while multiple projects compete for limited staff with multiple skills. A two-stage decomposition model, including an initial local scheduling stage and a global coordination stage, is established to describe this problem. Then, a two-stage approach with softmax scoring mechanism (TSA-SSM) is proposed to solve the local schedule of minimizing the single-project makespan and the global coordination decision of minimizing the total tardiness cost (TTC). According to the local scheduling plan obtained by the forward–backward scheduling genetic algorithm (FBSGA), the softmax scoring mechanism uses a greedy assignment strategy to solve the resource conflicts in the global decision stage, which is combined with the characteristics of multi-skilled staff. Based on the collection of multi-project instances, some numerical experiments are carried out. The results show that our TSA-SSM gets better solutions to large-size and strong conflict instances than some distributed and centralized methods, which proves that our method can effectively coordinate the allocation of multi-skilled staff among multiple projects. In addition, further experiments show that our method is also suitable for solving de-coupled problems, and satisfactory results are obtained.

Recommendations for the Implementation of Hospital Based HTA in Poland: Lessons Learned From International Experience.

Introduction: The main challenge of modern hospitals is purchasing medical technologies. Hospital-based health technology assessments (HB-HTAs) are used in healthcare facilities around the world to support management boards in providing relevant technologies for patients. Aim: This study was undertaken to update the existing body of knowledge on the characteristics of HB-HTA systems/models in the selected European countries. Insights gained from this study were used to provide an optimal approach for implementing HB-HTA in Poland. Materials and methods: Firstly, we carried out a systematic review in PubMed and embase. Secondly, we searched for gray literature via the AdHopHTA online handbook and the design book of the AdHopHTA project, as well as literature describing healthcare systems provided by the WHO. Then, we conducted in-depth interviews with HB-HTA experts from four countries. Finally, we selected ten countries from Europe and prepared frameworks for data collection and analyses. Results: The selected countries (Switzerland, Spain, France, Italy, Denmark, Finland, Sweden, the Netherlands, and Austria) are examples of decentralized or deconcentrated healthcare systems. In terms of HB-HTA, differences in organisational models (independent group, stand-alone, integrated-essential, integrated-specialised), type of financing (internally vs. externally), collaboration with an HTA National Agency and other stakeholders (e.g., Patients’ Associations) were identified. HB-HTA engages multi-skilled staff with various academic backgrounds and operates mainly on a voluntary basis. Conclusion: Strengths and weaknesses associated with various organisational models must be carefully considered in the context of support for decentralized or centralized models of implementation while embarking on HTA activities in Polish hospitals.

Dataset for solving a hybrid flexibility strategy on personnel scheduling problem in the retail industry.

This data article describes datasets from a home improvement retail store located in Santiago, Chile. The datasets have been developed to simultaneously solve a staffing and tour scheduling problem that incorporates flexible contracts and multiskilled staff. This Data in Brief article is related to the published article “Hybrid flexibility strategy on personnel scheduling: Retail case study” [1]. The datasets contain real, processed, and simulated data. Regarding the real and processed datasets, they are presented for three different store sizes (4, 5 or 6 departments). Real datasets include information about the employment-contract characteristics, cost parameters, and a forecast of the number of employees required in each department for each day of the week and each time period into which the operating day is divided. As regards the data processed for the case study, they include the set of skill sets considering that the employees can be trained in a maximum of two store departments. Regarding the simulated datasets, they include information about the random parameter of staff demand in each store department. The simulated data are presented in 90 text files classified by: (i) Store size (4, 5 or 6 departments). (ii) Coefficient of variation (10, 20, 30%). (iii) Instance identification number (10 instances per scenario that resulted from combining the store sizes and coefficients of variation). Researchers can use the datasets for benchmarking the performance of different approaches with the one presented by Porto et al. [1], and in consequence, they can find solutions to the same (or similar) type of personnel scheduling problem. The dataset includes an Excel workbook that can be used to randomly generate staff demand instances according to a chosen coefficient of variation.

A competence-time-quality scheduling model of multi-skilled staff for IT project portfolio

Technical professionals are a key factor for IT product development. In an IT company, it is common for an employee to hold multiple skills. Multi-skilled staff increases the difficulty of project portfolio scheduling and staff assignment. This paper helps R&D managers cope with the problem by proposing a multi-objective optimization model of project portfolio scheduling and multi-skilled staff assignment. The model considers three objectives with strong practicality, i.e., staff skill enhancement, development cycle time, and product quality, and incorporates skill cultivation through a learning curve. We then propose an improved multi-objective Pareto ant colony optimization algorithm combining genetic operators to find an approximate Pareto solution set. Personalized decision rules with strong practicability are also discussed for selecting an appropriate solution. A case study in a leading electrical device company in China demonstrates the utility of the proposed model and algorithm.

Hybrid flexibility strategy on personnel scheduling: Retail case study

This study evaluates the potential benefits of incorporating labor flexibility into personnel scheduling. The solution methodology develops, in an innovative way, a hybrid strategy of labor flexibility that combines the following two flexibility strategies: (i) flexible contracts, which allow to relax the duration of the shifts and the number of weekly hours employees must work; and (ii) multiskilled staff, employees trained to work on multiple task types. A mixed integer linear programming model is proposed to determine how many employees are required in each type of contract, and how many of them will be multiskilled employees and in which task types. Results using real data from a Chilean retail firm show the potential benefits of the proposed hybrid flexibility strategy in relation to experiments where flexibility is not considered (i.e., without flexible contracts and multiskilling), or even, when scenarios consider only one of the two flexibility strategies. The increases in the number of multiskilled employees are mainly produced by demand variability than by their respective size. Regarding the staff composition, empirical results show that on average the proportion of full-time employees with respect to part-time employees is approximately 1:3. It is also shown that the most attractive contracts are those that have short workdays.

A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution

We address a multi-skill project scheduling problem for IT product development in this article. The goal is for product development managers to be able to generate an initial schedule at an early stage of development activities. Due to the complexity of the product structure and functionality, an IT product development effort is divided into multiple projects. Each project includes several tasks, and each task must be completed by an employee who has mastered a certain skill to complete it. A pool of multi-skilled employees is available, and the employees’ skill efficiencies are influenced by both learning and forgetting phenomena. Based on the real-world demands of product development managers, three objectives are simultaneously considered: skill efficiency gain, product development cycle time and costs. To solve this problem, we propose a multi-objective non-linear mixed integer programming model. The Non-dominated Sorting Genetic Algorithm II (NSGA-II)is designed to generate an approximation to the optimal Pareto front of this NP-hard multi-objective optimisation problem. The algorithm produces feasible schedules for all the development projects using the serial schedule generation scheme. We adopt penalty values and individual employee adjustments to address resource conflicts and constraint violations. A weighted ideal point method is used to select the final solution from the approximate Pareto solution set. An application case of a new electrical energy saving product implementation in a leading electrical device company in China is used to illustrate the proposed model and algorithm.

P6.066 Where Are We Now and Where Are We Going?: A Meta-Analysis of 10 Years of Sexual Health Service Integration in Glasgow, Scotland, UK

BackgroundIn 2000, family planning and reproductive health, genitourinary medicine, and women’s health converged to form integrated sexual health services in Glasgow and Clyde, Scotland - the first large-scale UK example....

Day case and short stay surgery: 2

Day case and short stay surgery: 2

The Link between Operations Strategy and Human Resource Management for NGOs Working in Unstable Environments

This article discusses the link between operations strategy and strategic human resources management for non-government organisations. Human resources are a great asset for NGO to plan and implement their operations strategies. The article shows how HRM should be proactive and responsive to any changes in the operational environment. Strategic human resource management could lead to organisation’s competitive advantage. It also enables more effective stakeholder interaction and leads to better efficiencies in implementation of operations strategy. Strategic HRM can create multi-skilled staff, who can easily be tuned to implement various activities. IT and HR are intrinsically linked in execution of operations strategy. The example given from Iraq about NGO staff operating in unstable context shows how HRM should be proactive and responsive to meet operations targets.

The Impact of Multi-Skilled Staff Availability on Day Surgery Cancellations

This paper outlines a study undertaken by Helen Lloyd to assess the impact of multi-skilled theatre practitioners on reducing cancellations in stand alone day surgery units in England and Wales. The author provides the background to the study together with an overview of the results. The literature review undertaken before the study is published in full. It identifies what factors influence the efficiency of day surgery and operating theatre facilities, traditional staffing of operating theatres and day surgery facilities, together with other influencing factors for theatre utilisation. The author recieved partial funding from ERFF to complete her MBA in Health Service Management at Greenwich School of Management (accredited to University of Hull) in 2007.

The Multi-Skilled Day Surgery Practitioner

This article will explore the concept of multi-skilled staff within Jersey general hospital's day surgery unit. The role, specific to day surgery, is discussed as are the driving factors behind multi-skilling. The benefits of multi-skilling to the practitioner, to the client and to the unit are considered. The importance and the role of a training coordinator who facilitates the multi-skilling ethos is also discussed.

Changes in Long-Term Care for Elderly People with Dementia

SUMMARY Recent changes in dementia care in Canada, based primarily on successes in Sweden and Australia, include clustering small numbers of residents together, delivering care in a flexible and individualized manner, and permanent scheduling of front line multi-skilled staff. This model, generically referred to as “resident-centred” care, has been embraced by practice leaders across Canada, and yet there remain challenges to its implementation in the front lines. An exploratory, qualitative study focussing on front line workers' experience in British Columbia was conducted in 2000. Results revealed five key barriers to full implementation of resident-centred dementia care: workload, resistance to change at all levels, operational realities, resident characteristics, and the design and scale of the built environment. Keys to successfully implementing this approach were identified as: higher staff-to-resident ratios, effective leadership, formal involvement of front line staff in decision making, on-going ...

Modeling staffing flexibility: A case of China

This paper presents a multi-skilled staff planning model that considers staff flexibility. The primary purpose of this research is to develop a representative staff planning model which captures the balance of cost and benefits of staff flexibility for a service facility. Multiple objective goal programming (GP) method has been applied to analyze several diversified goals. The model has general applications in many service organizations. An example case of a Chinese clinic has been analyzed and a simulation experiment has been designed to investigate managerial insights of staff flexibility.

Strategies and measurement for workforce flexibility: an application of functional flexibility in a service setting

In situations where a volatile product market meets an unstable labour market, as is often found in customer contact service operations such as the hospitality industry, there is a need for the constant manipulation of labour supply to match labour demand. Functional workforce flexibility, where multiskilled staff are able to move from jobs in one department to jobs in another, presents an opportunity for solving part of the problem. Presents an approach to calculating the need for functional flexibility dependent on the identified discrepancies in labour demand and supply. Having identified the size of the need, a strategy needs to be developed for fulfilling that need. In implementing this strategy, two approaches are identified: planned whole job substitution and boundary loosening. While the planned approach offers the rational course for maintaining quality and productivity levels, there is evidence that an evolving approach may help to stabilize a highly volatile situation by breaking down barriers from within.