Radio Communications Interdiction Problem under deterministic and probabilistic jamming

•Introduce the Radio Communications Interdiction Problem.•Study deterministic and probabilistic variations of RCIP.•Approximate nonlinearity in the jamming probability function.•Solve the resulting bilevel formulations using decomposition. The Radio Communications Interdiction Problem (RCIP) seeks t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computers & operations research 2019-07, Vol.107, p.200-217
Hauptverfasser: Tanergüçlü, Türker, Karaşan, Oya Ekin, Akgün, İbrahim, Karaşan, Ezhan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Introduce the Radio Communications Interdiction Problem.•Study deterministic and probabilistic variations of RCIP.•Approximate nonlinearity in the jamming probability function.•Solve the resulting bilevel formulations using decomposition. The Radio Communications Interdiction Problem (RCIP) seeks to identify the locations of transmitters on the battlefield that will lead to a robust radio communications network by anticipating the effects of intentional radio jamming attacks used by an adversary during electronic warfare. RCIP is a sequential game defined between two opponents that target each other’s military units in a conventional warfare. First, a defender locates a limited number of transmitters on the defender’s side of the battlefield to optimize the relay of information among its units. After observing the locations of radio transmitters, an attacker locates a limited number of radio jammers on the attacker’s side to disrupt the communication network of the defender. We formulate RCIP as a binary bilevel (max–min) programming problem, present the equivalent single level formulation, and propose an exact solution method using a decomposition scheme. We enhance the performance of the algorithm by utilizing dominance relations, preprocessing, and initial starting heuristics. To reflect a more realistic jamming representation, we also introduce the probabilistic version of RCIP where a jamming probability is associated at each receiver site as a function of the prevalent jamming to signal ratios leading to an expected coverage of receivers as an objective function. We approximate the nonlinearity in the jamming probability function using a piecewise linear convex function and solve this version by adapting the decomposition algorithm constructed for RCIP. Our extensive computational results on realistic scenarios show the efficacy of the solution approaches and provide valuable tactical insights.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2019.03.013