Dynamic Asset Allocation Approaches for Counter-Piracy Operations

Abstract

Piracy on the high seas is a problem of world-wide concern. In response to this threat, the US Navy has developed a visualization tool known as the Pirate Attack Risk Surface (PARS) that integrates intelligence data, commercial shipping routes, and meteorological and oceanographic (METOC) information to predict regions where pirates may be present and where they may strike next. This paper proposes an algorithmic augmentation or add-on to PARS that allocates interdiction and surveillance assets so as to minimize the likelihood of a successful pirate attack over a fixed planning horizon. This augmentation, viewed as a tool for human planners, can be mapped closely to the decision support layer of the Battlespace on Demand (BonD) framework [32]. Our solution approach decomposes this NPhard optimization problem into two sequential phases. In Phase I, we solve the problem of allocating only the interdiction assets, such that regions with high cumulative probability of attack over the planning horizon are maximally covered.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2012
Accession Number
ADA617784

Entities

People

  • David Lee Kleinman
  • David Sidoti
  • Diego Fernando Martínez Ayala
  • Eva D. Regnier
  • James A. Hansen
  • Krishna R. Pattipati
  • Manisha Mishra
  • Woosun An
  • Xu Han

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Computational Complexity
  • Computer Programming
  • Detection
  • Dynamic Programming
  • Evolutionary Algorithms
  • Helicopters
  • Interdiction
  • Intervals
  • Multiple Targets
  • Optimization
  • Probability
  • Stochastic Control
  • Surveillance
  • Time Intervals
  • United States

Readers

  • Atmospheric Science/Meteorology
  • Military History / Militaries and War Studies
  • Operations Research