Abstract: Hot rolling production planning is a key link in the iron and steel manufacturing process, involving product delivery fulfillment, capacity balance of multi-line and multi-process resources, and achievement of product specifications, properties, and quality. The level of planning optimization directly affects cost reduction, efficiency improvement, energy saving, and carbon reduction in steel enterprises. This paper analyzes the current status and research progress of production planning methods for hot-rolled coils and medium-heavy plates from the perspective of the steel production process. Considering the evolution of research objects and methods, as well as the difficulties in engineering applications, the paper discusses potential enabling approaches of intelligent optimization technologies, such as industrial big data and deep learning, under the new demands for high-end, intelligent, and green development of steel enterprises. Furthermore, the common trends in the development of production planning models for hot-rolled coils and medium-heavy plates are summarized. Key collaborative optimization issues are discussed, including steelmaking-continuous casting-hot rolling coordination, slab yard and reheating furnace coordination, and virtual-real slab collaborative planning. It is suggested that future research should focus on complex combinatorial sequencing optimization with multi-objective trade-offs and dynamically adjustable complex constraints, so as to develop a human-machine collaborative optimization method driven by the coupling of business rules, intelligent models, and dynamic data. This paper provides new ideas for research and industrial application of hot rolling production planning optimization methods in the iron and steel industry.