Optimization of Production and Packaging Schedules Using Declarative Approaches: Application to a Food Manufacturing Plant

Production scheduling in food manufacturing is challenging due to the interaction of resource limitations, strict quality requirements, and demanding delivery commitments. This thesis tackles these issues through the design and deployment of an advanced optimization system for scheduling gluten-free pasta production. The work is based on a real industrial case involving multi-stage workflows, heterogeneous machinery, and tight temporal constraints driven by product quality and allergen-management standards. The scheduling problem is formalized as a comprehensive model that captures production line assignment, sequencing of operations, intermediate storage dynamics, and coordination with packaging activities. The formulation incorporates industry-specific aspects such as drying processes, silo capacity constraints, sequence-dependent setups, customer deadlines, and business rules including alternating packaging modes, frozen orders, and recipe-based grouping. The model is implemented within a modern constraint-based optimization framework and supported by dedicated strategies for handling large instances and ensuring robust performance. A complete data-integration pipeline connects the system with enterprise resources, while a web-based interface enables planners to configure optimization runs, visualize schedules through interactive Gantt charts, and analyze performance indicators. Evaluation on real production data demonstrates the practical value of the proposed approach. The thesis contributes both to the understanding of complex scheduling in food manufacturing and to the effective adoption of optimization technology in industrial environments. The resulting framework supports continuous improvement in production planning and offers insights applicable to similar process-industry scenarios.