Integrated Scheduling and Material Handling: Theory and Applications in Manufacturing Systems

Scheduling concerns the allocation of limited resources to competing tasks over time and is central to manufacturing systems. In practice, production scheduling is tightly linked to material handling, as jobs must be transported between machines, buffers, and storage locations. However, transportation decisions have often been simplified or decoupled from classical scheduling models. This dissertation investigates the problem of Integrated Scheduling and Material Handling (ISMH), where processing and transportation decisions are jointly optimized to improve overall system performance. The thesis develops this objective in three steps. First, it provides a structured and unified classification of scheduling problems with transportation elements, organizing a fragmented body of literature and clarifying methodological foundations. Second, it studies scheduling in AGV-based material handling systems under battery constraints, proposing a novel mixed-integer programming formulation and an exact solution approach based on logic-based Benders decomposition. Third, it extends integrated models to a buffer-constrained flow shop setting with mobile buffering, introducing a decomposition-based algorithm that significantly improves scalability. Together, these contributions advance conceptual understanding, modeling frameworks, and exact solution methods for integrated production and internal logistics planning in modern manufacturing systems.