Improving Workforce Scheduling in a Food Manufacturing Plant Considering Employee Skills and Daily Production Operations Using Integer Programming

Abstract

Optimal human resource allocation is one of the key challenges in production and operations management, directly affecting process efficiency, productivity, and quality. Despite the development of various models and approaches to improve workforce allocation, many of these models have limited practical applicability due to excessive simplification and insufficient consideration of the real needs and constraints of organizations. The dairy industry, characterized by product diversity, sinusoidal demand fluctuations, the necessity of adjusting production schedules during the process, and limitations in long-term planning, represents a clear example of complex production environments that require a dynamic, flexible, and rapid model for human resource allocation. In this study, an integer programming-based model is proposed, enabling the optimal assignment of available workers to daily tasks while considering their expertise, the importance of activities, and operational constraints. The proposed model, with a simple and implementable structure in a real-world environment, generates workforce allocation plans in the shortest possible time. Experimental results across different factory shifts indicate that the resulting allocations fully align with the evaluations of production managers and experts, providing a highly effective allocation pattern. Moreover, this approach can serve as a practical framework to enhance operational decision-making in other industries with similar characteristics.