Modellering av framtida markstrid : Vidareutveckling av modell för fördröjningsstrid

In military tactics, delay operations play a crucial role in weakening an advancing adversary, gaining time, and improving conditions for future engagements. This thesis extends a previously developed delay combat model based on Lanchester equations, which simulates a defending force engaging a superior attacker across multiple contact points separated by transport phases. The model focuses on optimizing how limited defensive resources are allocated across these contact points to best fulfill the objectives of delay operations: maximizing time gained, inflicting attrition on the attacker, and preserving own forces. The extensions introduced in this work include stochastic combat effects, dynamic retreat decisions, unit regrouping, attacker fatigue, coordination modeling using Kuramoto networks, and adaptive transport delays. These additions are evaluated in terms of their impact on the resulting optimal allocation strategies relative to the original model. Results show that several of the introduced extensions significantly affect the optimal allocation strategy. The original model tended to favor concentrated allocations, where all resources were placed at a single contact point. However, extensions such as attacker fatigue, transport-related extensions and stochastic combat dynamics shifted the optimal strategy toward more distributed allocations. Unit regrouping after retreats created strong incentives to engage the enemy early, while adaptive retreat logic enabled withdrawal behavior that adapts to ongoing combat developments. Coordination effects showed limited influence on optimal allocation under the tested parameters but warrant further investigation. Further work should focus on validating and calibrating the model, as well as combining the developed extensions.