Island archipelago ferry networks face a distinctive set of operational challenges: aging fleets, growing demand, geographic constraints that limit vessel size, and mounting pressure to reduce fuel consumption and emissions. Addressing these challenges requires moving beyond incremental improvements toward a fundamental rethinking of how ferry networks are designed and scheduled. This project develops a suite of optimization-based planning tools to support that transition, using the Åland archipelago as a real-world case study. The core objective is to compare an existing ferry network against a proposed redesign, evaluating the operational and environmental implications of shifting from longer, multi-stop routes to shorter, higher-frequency segments connecting pairs of terminals. This structural change introduces a key trade-off: while shorter ferry legs can improve capacity utilization and reduce fuel consumption at sea, they may induce additional road travel between consecutive crossings, partially offsetting emissions gains. Quantifying and navigating this trade-off is central to the analysis. The mathematical framework integrates three interdependent planning layers (service scheduling, traffic flow assignment across a multimodal network, and system capacity sizing) within a unified Mixed-Integer Programming (MIP) formulation. The model supports multiple stakeholder perspectives, balancing operator cost efficiency against passenger and freight service quality, while explicitly accounting for emissions from both maritime and road transport. Schedule designs can be differentiated by day type and season to reflect varying demand patterns. We envision the model to be computationally demanding to be solved with commercial solvers directly, and we also plan to explore decomposition-based solution methods such as Dantzig-Wolfe or Benders decomposition to achieve solution quality at scale. Potentially, the project further explores extensions including fuel consumption modeling, alternative network configurations, booking system integration, and electrification potential assessment. Beyond the specific case study, the methods and tools developed are intended to be transferable to analogous ferry network planning contexts, contributing both practical decision-support capabilities and broader academic knowledge in multimodal transport optimization.