Name
Abstract | ||
|---|---|---|
Intelligence collection, while critical in mission planning, lacks systematic means to quantify its value for optimal prioritization. This work proposes a framework that starts with analyzing the plausible impacts imposed on assets and mission due to predicted adversary activities. The candidate collection requirements, derived from plausible futures, are evaluated for their benefits to mitigate potential impact to mission success. A Mixed Integer Programming problem is formulated to model the tradeoff between maximizing mission impact mitigation and satisfying resource constraints. A case study is presented to demonstrate the effectiveness of the framework, where insights are obtained based on the optimal solutions. |
Year | Venue | Keywords |
|---|---|---|
2011 | Fusion | optimisation,predicted adversary activities,mission success,plausible impact analysis,mission planning,intelligence collection,mixed integer programming problem,planing,optimal prioritization,optimizing collection requirements,sensor fusion,satisfiability,servers,finance,terrorism |
Field | DocType | ISBN |
Computer science,Futures contract,Server,Prioritization,Operations research,Sensor fusion,Integer programming,Adversary | Conference | 978-1-4577-0267-9 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khiem Tong | 1 | 0 | 0.34 |
| Shanchieh Jay Yang | 2 | 131 | 23.11 |
| Moises Sudit | 3 | 159 | 16.55 |
| Jared Holsopple | 4 | 52 | 4.31 |