A greedy heuristic approach for the project scheduling with labour allocation problem

Responding to the growing need of generating a robust project scheduling, in this article we present a greedy algorithm to generate the project baseline schedule. The robustness achieved by integrating two dimensions of the human resources flexibilities. The first is the operators’ polyvalence, i.e. each operator has one or more secondary skill(s) beside his principal one, his mastering level being characterized by a factor we call “efficiency”. The second refers to the working time modulation, i.e. the workers have a flexible time-table that may vary on a daily or weekly basis respecting annualized working strategy. Moreover, the activity processing time is a non-increasing function of the number of workforce allocated to create it, also of their heterogynous working efficiencies. This modelling approach has led to a nonlinear optimization model with mixed variables. We present: the problem under study, the greedy algorithm used to solve it, and then results in comparison with those of the genetic algorithms

Flexible resources allocation techniques: characteristics and modelling

At the interface between engineering, economics, social sciences and humanities, industrial engineering aims to provide answers to various sectors of business problems. One of these problems is the adjustment between the workload needed by the work to be realised and the availability of the company resources. The objective of this work is to help to find a methodology for the allocation of flexible human resources in industrial activities planning and scheduling. This model takes into account two levers of flexibility, one related to the working time modulation, and the other to the varieties of tasks that can be performed by a given resource (multi–skilled actor). On the one hand, multi–skilled actors will help to guide the various choices of the allocation to appreciate the impact of these choices on the tasks durations. On the other hand, the working time modulation that allows actors to have a work planning varying according to the workload which the company has to face

Leadership Strategies to Reduce Employees\u27 Occupational Stress

Job-related aspects of the work environment, such as work pressure, workload, leadership, and management support cause occupational stress and increase costs to organizations. Grounded in the job demands-resources model theory, the purpose of this single case study was to explore strategies some bank managers use to reduce employees\u27 occupational stress. The interview process included 5 managers employed at a bank in the Caribbean who successfully implemented strategies that reduced employees\u27 occupational stress. The data collection and analysis process involved face-to-face, semistructured interviews and analysis of organizational documentation. Using the exploratory approach in data analysis, data were systematically integrated, evaluated, and summarized through a process of coding and generating themes and patterns. During the coding process, 4 major themes emerged: organizational protection and leadership, supportive organization, occupational health and well-being, and prevention. Business managers who develop and execute strategies centered on these themes might reduce job-related stress factors and the negative consequences of occupational stress. The study results might prompt business leaders to develop prevention strategies to address the causes of potential stressors linked to work conditions. The implications for positive social change include the potential for improving employee health and reducing health costs to employees, their families, and communities

Why do health workers in rural Tanzania prefer public sector employment?

Severe shortages of qualified health workers and geographical imbalances in the workforce in many low-income countries require the national health sector management to closely monitor and address issues related to the distribution of health workers across various types of health facilities. This article discusses health workers' preferences for workplace and their perceptions and experiences of the differences in working conditions in the public health sector versus the church-run health facilities in Tanzania. The broader aim is to generate knowledge that can add to debates on health sector management in low-income contexts. The study has a qualitative study design to elicit in-depth information on health workers' preferences for workplace. The data comprise ten focus group discussions (FGDs) and 29 in-depth interviews (IDIs) with auxiliary staff, nursing staff, clinicians and administrators in the public health sector and in a large church-run hospital in a rural district in Tanzania. The study has an ethnographic backdrop based on earlier long-term fieldwork in Tanzania. The study found a clear preference for public sector employment. This was associated with health worker rights and access to various benefits offered to health workers in government service, particularly the favourable pension schemes providing economic security in old age. Health workers acknowledged that church-run hospitals generally were better equipped and provided better quality patient care, but these concerns tended to be outweighed by the financial assets of public sector employment. In addition to the sector specific differences, family concerns emerged as important in decisions on workplace. The preference for public sector employment among health workers shown in this study seems to be associated primarily with the favourable pension scheme. The overall shortage of health workers and the distribution between health facilities is a challenge in a resource constrained health system where church-run health facilities are vital in the provision of health care in rural areas and where patients tend to prefer these services. In order to ensure equity in distribution of qualified health workers in Tanzania, a national regulation and legislation of the pension schemes is required

work sequence analysis and computer simulations of value flow and workers relocations a case study

Abstract Several solutions have been proposed for the workload balancing in manual assembly lines with workers' task assignment. Facing the case study of a sheet metal assembly line of transport pallets, the paper addresses the problem of the dynamic task assignment. The walking path minimization is considered in the problem, together with task sequence constraints. A real-time simulation allows to test the solution variations before their implementation

New matrix methodology for algorithmic transparency in assembly line balancing using a genetic algorithm

© 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/This article focuses on the Mixed-Model Assembly Line Balancing single-target problem of type 2 with single-sided linear assembly line configurations, which is common in the industrial environment of small and medium-sized enterprises (SMEs). The main objective is to achieve Algorithmic Transparency (AT) when using Genetic Algorithms for the resolution of balancing operation times. This is done by means of a new matrix methodology that requires working with product functionalities instead of product references. The achieved AT makes it easier for process engineers to interpret the obtained solutions using Genetic Algorithms and the factors that influence decisions made by algorithms, thereby helping in the later decision-making process. Additionally, through the proposed new matrix methodology, the computational cost is reduced with respect to the stand-alone use of Genetic Algorithms. The AT produced using the new matrix methodology is validated through its application in an industry-based paradigmatic example.Peer ReviewedPostprint (published version

The impact of artificial intelligence on the nature and quality of jobs. Bruegel WORKING PAPER | ISSUE 14/2022 | 27 JULY 2022.

Artificial intelligence (AI), like any workplace technology, changes the division of labour in an organisation and the resulting design of jobs. When used as an automation technology, AI changes the bundle of tasks that make up an occupation. In this case, implications for job quality depend on the (re)composition of those tasks. When AI automates management tasks, known as algorithmic management, the consequences extend into workers’ control over their work, with impacts on their autonomy, skill use and workload. We identify four use cases of algorithmic management that impact the design and quality of jobs: algorithmic work-method instructions; algorithmic scheduling of shifts and tasks; algorithmic surveillance, evaluation and discipline; and algorithmic coordination across tasks. Reviewing the existing empirical evidence on automation and algorithmic management shows significant impact on job quality across a wide range of jobs and employment settings. While each AI use case has its own particular effects on job demands and resources, the effects tend to be more negative for the more prescriptive (as opposed to supportive) use cases. These changes in job design demonstrably affect the social and physical environment of work and put pressure on contractual employment conditions as well. As technology development is a product of power in organisations, it replicates existing power dynamics in society. Consequently, disadvantaged groups suffer more of the negative consequences of AI, risking further job-quality polarisation across socioeconomic groups. Meaningful worker participation in the adoption of workplace AI is critical to mitigate the potentially negative effects of AI adoption on workers, and can help achieve fair and transparent AI systems with human oversight. Policymakers should strengthen the role of social partners in the adoption of AI technology to protect workers’ bargaining power

Hyper‐Precarious Lives: Understanding Migration, Global Supply Chain, and Gender Dynamics in Bangladesh

This article examines the lived experiences of precarity in Bangladesh's ready‐made garments (RMG) industry, focusing on female migrant workers employed in Dhaka and surrounding industrial areas. Over the past three decades, the growth of the RMG sector has attracted economically disadvantaged rural women, distancing them from their traditional domestic and agricultural roles. This sector predominantly employs young women due to their perceived flexibility, low wages, and limited union involvement. Additionally, their status as “unskilled” workers in the lowest echelons of a gender‐stratified labour market, along with the influence of socio‐cultural power dynamics, constrains their capacity to negotiate their positions effectively. Drawing on in‐depth ethnographic research conducted in Dhaka and Gazipur, this article unravels the intricate interplay between insecure labour conditions, the impact of the global supply chain, and gender dynamics. It underscores the pivotal significance of socio‐cultural power dynamics in understanding the vulnerability experienced by female migrant labourers. We assert that a comprehensive understanding of precarious work requires recognising the inherent link between precarious employment and precarious life within the broader context of socio‐cultural power dynamics, gender norms, and societal relations