Abstract
Maritime security operations, such as counter-piracy operations, often take place in vast areas of open sea. This requires operating in a coalition task force consisting of multiple task units, each composed of a number of naval assets such as frigates, helicopters, and unmanned aerial vehicles (UAVs). For the planning of these operations, we introduce a two-level approach. At the first level, the area of operations is divided into sectors and the available task units are assigned to these sectors. The second level consists of the tactical planning of the deployment of the individual assets of a task unit within the task unit’s sector. In this paper, we propose algorithms to tackle both levels of planning. For maritime security operations in general, we introduce an allocation algorithm for dividing an area of operations, based on the capabilities of the individual task units, in such a way that the expected effectiveness of the task force as a whole is optimal. For counter-piracy operations, where the focus is on the prevention of pirate attacks on merchant vessels, a search planning algorithm is introduced that allows generating effective search plans for the deployment of the task unit’s assets within a sector of the area of operations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
For describing the organization structure, we use the terminology from Defensie 2014, Chapter 5, except for “task element”, which we will simply call “asset”.
- 2.
See Defensie 2014, pp. 114–115.
- 3.
See Smith and Van Dongen 2015.
- 4.
See Johnson et al. 1989.
- 5.
See Cattrysse and Van Wassenhove 1992.
- 6.
Note that, since we assume that the sizes of the area and the sectors are integer multiples of a certain unit of length, the number of possible partitions is finite.
- 7.
- 8.
If there are empty sectors, it is also possible to randomly move a task unit to an empty sector.
- 9.
See Fitski et al. 2015.
- 10.
The recognized surface picture or RSP is a listing of the surface ships within a certain area, with additional information for each ship, such as position, speed, course, and ship type.
- 11.
In SURPASS, it is possible to define IDCRITS using either the NATO Standard Identities (Unknown, Assumed Friend, Suspect, Friend, Neutral, Hostile) or the Maritime Interdiction Force (MIF) Identities (Contact Of Interest, Assessed Cleared Vessel, Suspicious Vessel, Potential Violator Vessel, Cleared Vessel, Critical Contact Of Interest).
- 12.
It must be noted that the sectors do not fully correspond to “covered” area, since an asset that is near the border of its sector might perform detections outside its sector. In SURPASS, an asset is not allowed to move outside its sector, but it can already start intercepting a target that it detected outside its sector.
- 13.
- 14.
See Fitski 2013.
- 15.
In this equation, we define 00 = 1.
- 16.
See Vermeulen and Van Veldhoven 2014.
References
Atkinson MP, Kress M, Szechtman R (2017) To Catch an Intruder: Part A - Uncluttered Scenario. Wiley Online Library https://doi.org/10.1002/nav.21730
Cattrysse DG, Van Wassenhove LN (1992) A survey of algorithms for the generalized assignment problem. European Journal of Operational Research 60:260–272
Defensie (2014) Grondslagen van het Maritieme Optreden, Nederlandse maritiem-militaire doctrine. Ministerie van Defensie, The Hague
Fitski HJ (2013) Effectiviteitsmaten voor counter piracy, counter smuggling en counter illegal fishing. TNO, The Hague
Fitski HJ, Van Veldhoven ER, Nienhuis B (2015) Simulatie van maritieme oppervlaktebeeldopbouw met SURPASS. Militaire Spectator 184:14–24
Henderson D, Jacobson SH, Johnson AW (2003) The Theory and Practice of Simulated Annealing. In: Glover F, Kochenberger GA (eds) Handbook of Metaheuristics. Springer, Boston MA
Johnson DS, Aragon CR, McGeoch LA, Schevon C (1989) Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning, Operations Research 37:865–892
Kirkpatrick S, Gelatt Jr CD, Vecchi MP (1983) Optimization by Simulated Annealing. Science 220:671–680
Laan CM, Barros AI, Boucherie RJ, Monsuur H (2017) Security Games with Probabilistic Constraints on the Agent’s Strategy. In: Rass S, An B, Kiekintveld C, Fang F, Schauer S (eds) Decision and Game Theory for Security. Springer, Cham, pp 481–493
Smith AJE, Van Dongen MPFM (2015) Programme V1114 MSA - Final Report. TNO, The Hague
Vermeulen JFJ, Van Veldhoven ER (2014) Sector Search Algorithm for Maritime Situational Awareness. TNO, The Hague
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 T.M.C. Asser press and the authors
About this chapter
Cite this chapter
van Veldhoven, E.R., Fitski, H.J. (2018). Optimizing Asset Deployment in Maritime Law Enforcement. In: Monsuur, H., Jansen, J., Marchal, F. (eds) NL ARMS Netherlands Annual Review of Military Studies 2018. NL ARMS. T.M.C. Asser Press, The Hague. https://doi.org/10.1007/978-94-6265-246-0_8
Download citation
DOI: https://doi.org/10.1007/978-94-6265-246-0_8
Published:
Publisher Name: T.M.C. Asser Press, The Hague
Print ISBN: 978-94-6265-245-3
Online ISBN: 978-94-6265-246-0
eBook Packages: Law and CriminologyLaw and Criminology (R0)