Modelling host population support for combat adversaries

Mathew Zuparic, Sergiy Shelyag, Maia Angelova, Ye Zhu and Alexander Kalloniatis

Journal of the Operational Research Society, 2023, vol. 74, issue 3, 928-943

Abstract: We consider a model of adversarial dynamics consisting of three populations, labelled Blue, Green, and Red, which evolve under a system of first order nonlinear differential equations. Red and Blue populations are adversaries and interact via a set of Lanchester combat laws. Green is divided into three sub-populations: Red supporters, Blue supporters, and Neutral. Green support for Red and Blue leads to more combat effectiveness for either side. From Green’s perspective, if either Red or Blue exceeds a size according to the capacity of the local population to facilitate or tolerate, then support for that side diminishes; the corresponding Green population reverts to the neutral sub-population, who do not contribute to combat effectiveness of either side. The mechanism for supporters deciding if either Blue or Red is too big is given by a logistic-type interaction term. The intent of the model is to examine the role of influence in complex adversarial situations typical in counter-insurgency, where victory requires a genuine balance between maintaining combat effectiveness and support from a third party whose backing is not always assured.

Date: 2023
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DOI: 10.1080/01605682.2022.2122736

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