Logistics Systems in Industrial Engineering: An Operations Research Perspective

Abstract

Modern logistics systems require coordinated decisions across production, inventory, warehousing, transportation, and supply networks. This narrative literature review examines these systems from an operations research (OR) perspective within industrial engineering. It summarizes the role of deterministic optimization, stochastic models, simulation, heuristics, and learning-assisted methods. It then reviews their applications in supply chain network design, inventory management, production scheduling, and warehouse optimization. The review shows that OR is most valuable when logistics is treated as an integrated system rather than a set of isolated activities. Traditional models remain essential for structured and stable problems, while uncertain and dynamic environments increasingly require adaptive, data-supported approaches. Future progress will depend on real-time model updating, multi-objective decision-making, and digital twins, as well as the integration of intelligent methods with explicit OR constraints and system-level objectives.