Considerations for Cross Domain / Mission Resource Allocation and Replanning

NPS NRP Technical ReportNaval platforms are inherently multi-mission - they execute a variety of missions simultaneously. Ships, submarines, and aircraft support multiple missions across domains, such as integrated air and missile defense, ballistic missile defense, anti-submarine warfare, strike operations, naval fires in support of ground operations, and intelligence, surveillance, and reconnaissance. Scheduling and position of these multi-mission platforms is problematic since one warfare area commander desires one position and schedule, while another may have a completely different approach. Commanders struggle to decide and adjudicate these conflicts, because there is plenty of uncertainty about the enemy and the environment. This project will explore emerging innovative data analytic technologies to optimize naval resource allocation and replanning across mission domains. NPS proposes a study that will evaluate the following three solution concepts for this application: (1) game theory, (2) machine learning, and (3) wargaming. The study will first identify a set of operational scenarios that involve distributed and diverse naval platforms and resources and a threat situation that requires multiple concurrent missions in multiple domains. The NPS team will use these scenarios to evaluate the three solution concepts and their applicability to supporting resource allocation and replanning. This project will provide valuable insights into innovative data analytic solution concepts to tackle the Navy's challenge of conducing multiple missions with cross-domain resources.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

APPLYING ARTIFICIAL INTELLIGENCE FOR IMPROVING SITUATIONAL AWARENESS AND THREAT MONITORING AT SEA AS KEY FACTOR FOR SUCCESS IN NAVAL OPERATION

The vast and dynamic maritime domain demands constant observance and accurate information for successful naval operations. However, traditional methods struggle to keep pace with the ever-increasing complexity and data overflow. The paper explores how Artificial Intelligence (AI) presents a transformative opportunity, significantly impacting naval operation by enhancing Situational awareness (SA) and Threat monitoring (TM). It is analyzed the impact of AI across three key areas: enhanced data processing and analysis, improved anomaly detection and predictive capabilities, and real-time decision support. By analyzing key principles, tactics, and procedures for AI implementation, it is explored the process how these capabilities can convert into practical applications and benefits. Examples like AI-powered maritime surveillance and predictive systems for naval assets demonstrate solid benefits of this technological progress. Additionally, in the paper are envisioned future operational scenarios where AI-driven autonomous systems and dynamic route optimization become commonplace. The analysis demonstrates how AI can be a critical factor in moving naval operations into a new era of efficiency and proactive threat management. However, responsible development and ethical considerations remain of paramount importance

Incorporating intelligence-led policing in integrated cross-border maritime law enforcement operations in British Columbia

British Columbia shares a southern maritime border with Washington State that bisects the Gulf Islands from the San Juan Islands. The RCMP is responsible for the maritime border security between ports of entry. Challenges to maritime border enforcement include a lack of marine domain awareness, globalization, terrorism, transnational organized crime and drug trafficking, criminal networks, and jurisdictional issues. The RCMP have partnered with the US Coast Guard to enforce cross-border criminality in a program called the Integrated Cross-border Maritime Law Enforcement Operations Act (ICMLEO), also referred to as Shiprider. The Shiprider program was implemented under the standard model of policing. By gathering and utilizing better information, adapting an intelligence-led approach, and leveraging technology, the Shiprider program could become more efficacious

Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Technical ReportThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order