This study systematically reviews the evolution, present focus, and future potential of floating ports/ harbours within the wider maritime industry. Using a bigram-based search strategy across Scopus and Web of Science, 884 relevant publications were identified, of which 140 directly addressed floating ports or related applications. A structured classification based on the “Elements of the Maritime Industry” framework revealed a strong concentration on construction aspects, with significant gaps in management, logistics, and ancillary activities. Keyword mapping through VOSviewer highlights a progression from safety-driven designs to sustainable, multifunctional, and climate-resilient infrastructures. In addition, the study introduces two working definitions; I) offshore floating ports and II) floating solutions for onshore/nearshore port infrastructure, to clarify emerging directions in the conceptual and functional development of floating port systems. The findings underline both the scarcity and growing importance of floating ports as a critical component of future maritime logistics and governance.

Planning of container terminal operations is a complex task, which requires the accurate scheduling of operations that are highly interrelated and uncertain. This study aims to investigate the integration of quayside operational planning functions under uncertain parameters by applying a reactive approach. A mixed integer linear programming (MILP) model is formulated to optimally assign and schedule quay cranes to multiple vessels simultaneously. The model will derive a baseline schedule that minimises the cost of waiting and departure delays of vessels. To address the uncertainty, a reactive strategy is formulated to generate a rescheduling plan when two types of disruptions, delays in vessel arrivals and quay crane breakdowns, occur during the operation. The reactive strategy will take the baseline schedule as input and derive a reactive schedule that minimizes the cost of deviations from the baseline schedule. The numerical experiments demonstrate the performance and effectiveness of the proposed approach to solve the integrated formulation under uncertainty.