Integrated Air and Missile Defence (IAMD) environments are increasingly characterized by high-density saturation attacks consisting of heterogeneous threats such as unmanned aerial systems, cruise missiles, and ballistic weapons. The core operational challenge is the Weapon-Target Assignment (WTA) problem, which involves determining the optimal allocation of defensive resources to incoming threats under strict time constraints. Traditional heuristic approaches implemented in legacy air defence systems rely on simplified rules such as Closest-Threat-First (CTF), which do not fully account for the multi-dimensional nature of modern engagements.

This paper proposes a Multi-Criteria Decision Analysis (MCDA) framework for optimizing WTA decisions in IAMD Command and Control (C2) systems. The model evaluates potential weapon-target engagements using three primary criteria: probability of interception, temporal urgency, and interceptor cost efficiency. A comparative simulation framework based on Monte Carlo methods evaluates the proposed approach against a baseline heuristic model. The results demonstrate that the MCDA-based approach significantly improves defensive efficiency while maintaining resource sustainability.

The presented Python-based simulation environment provides a scalable proof-of-concept for integrating decision-support algorithms into future automated IAMD architectures.