Purpose: This study aims to develop an Optimization-Based Maritime Governance Resilience Framework (OMG-RF) that integrates maritime security, strategic logistics, and governance resilience into a unified decision-support model to strengthen national resilience in maritime-dependent states.

Methodology: This study employs a quantitative operational research approach by combining the Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), multi-criteria decision-making, network optimization, and scenario-based simulation. An empirical evaluation was conducted using maritime traffic data, port performance indicators, and maritime disruption scenarios, including baseline, security disruption, logistics disruption, and combined disruption conditions.

Results: The findings reveal that Maritime Domain Awareness and Logistic Network Robustness are the most influential determinants of maritime governance resilience. The optimized governance framework reduced security risks by 28%, decreased logistics disruption costs by 34%, and lowered systemic vulnerability by 31%. In addition, the proposed model improves the system recovery speed by approximately 37% under combined disruption scenarios.

Conclusions: This study concludes that integrating optimization techniques into maritime governance significantly enhances resilience performance, improves maritime security continuity, and strengthens logistics network reliability under disruption conditions.

Limitations: This study is limited by the use of secondary data sources and simulation experiments focused only on selected strategic maritime corridors, which may restrict broader generalizations across different maritime environments.

Contributions: This study proposes a comprehensive optimization-based maritime governance framework that quantitatively integrates governance maturity, logistics resilience, and national security into a unified analytical model for evidence-based maritime policymaking.