Industrial and healthcare workforce scheduling for occupational safety, workload, and job satisfaction consideration

Effective workforce scheduling is crucial in human resource management across various industries. It offers potential improvements in cost savings, operational efficiency, employee well-being, and retention. This dissertation is dedicated to advancing the field of workforce scheduling by introducing innovative mathematical models and analytical solutions tailored for both the manufacturing industry and the healthcare sector, emphasizing worker well-being, safety, and job satisfaction.For industrial applications, our research focuses on the multifaceted benefits of job rotation in enhancing worker safety, promoting cross-training, and increasing job satisfaction. Two novel noise-safe job rotation scheduling models are introduced. The first model aims to ensure noise safety while optimizing production performance, considering worker-task skill matching within demand-driven manufacturing operations. This model can enhance a noise-safe work environment while maintaining promising operational performance. The second model incorporates skill development and personal attributes, including learning-forgetting rates and job boredom. This model addresses the complexities of balancing worker safety, skill development, and monotony-induced boredom. Such crucial aspects have a direct impact on production performance. Experiments showcase its capability to simultaneously achieve worker safety, multi-skill development, and reduced job monotony.In healthcare applications, this dissertation highlights the vital role of nurses’ job satisfaction in addressing the nursing shortage faced by hospitals worldwide. Two novel satisfaction-enhanced nurse scheduling models are presented. The first model seeks to accommodate individual nurse preferences for working slots and days off while ensuring equitable allocation of workload and preferred assignments. Building upon the first model, the second model incorporates a cost-effectiveness dimension to enhance practical applicability. Both models are validated using real-world data from hospitals in Thailand. The results highlight their effectiveness in generating more satisfactory and equitable work schedules within significantly reduced time compared to manually created schedules, with the second model offering cost-saving alternative scheduling plans.This dissertation offers up-to-date workforce scheduling approaches for industrial and healthcare sectors, emphasizing the significance of workforce scheduling in driving positive changes in working conditions. The workforce scheduling models introduced in this dissertation can serve as valuable decision-support tools to enhance safety, job satisfaction, and operational performance in practice. Furthermore, this dissertation contributes significantly to the fields of occupational safety, industrial human resource management, and healthcare personnel management, providing guidelines for future research aiming to bridge the theoretical and practical gaps in workforce scheduling research.