Abstract:

A LLM-driven multi-agent simulation model for production mobilization in the weapons and equipment supply chain is developed to address the practical challenge of transitioning the supply chain from peacetime to wartime production in response to surging wartime demand. The model consists of a military demand layer, a supply chain execution layer, and a mobilization decision-making layer. An LLM is incorporated as a mobilization decision generation module to represent the dynamic regulation of production conversion and expansion under war-readiness budget and production safety constraints. The simulation results show that compared with the no-mobilization and rule-based mobilization strategies, the LLM-based strategy achieves better delivery performance and a higher wartime order fulfillment rate. Embedding an LLM into the decision-making loop enables the simulation model to generate more adaptive mobilization strategies under constraints. The proposed method provides a feasible approach for simulation-based evaluation and decision-support analysis of production mobilization in the weapons and equipment supply chain.

Key words: weapons and equipment supply chain, production mobilization, large language model (LLM), multi-agent simulation, peacetime-to-wartime transition