TY - GEN
T1 - A Chain-of-Thought-Based Model Auto-Configuration Method for Customized Production Simulation
AU - Li, Na
AU - Laili, Yuanjun
AU - Ren, Lei
AU - Zhang, Lin
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - Simulation is a fundamental solution for investigating the capacity and efficiency of complex workshops in discrete manufacturing. With increasing custom production orders, it is more efficient to establish an extendable simulation model and make auto-configuration to analyze different kinds of reconfigurable production workspace, rather than construct a simulation model for each scenario. However, it is difficult to automatically configure a simulation model with long programming codes and complex coupled constraints among orders, materials, production machines, and production lines. To solve this problem, this paper establishes a key-value mapping rule to map key and repetitive information and decouple constraints among different parts of simulation model. Then, a chain-of-thought-based model auto-configuration method is proposed to configure a simulation model by using large-language model for programming code generation. To ensure correct and credible simulation model configuration, an automatic evaluation pipeline is also established. Experimental results on a typical extendable Anylogic simulation model for reconfigurable production workshop show that the proposed method can automatically generate appropriate simulation models for different scenarios with high precision greater than 90%.
AB - Simulation is a fundamental solution for investigating the capacity and efficiency of complex workshops in discrete manufacturing. With increasing custom production orders, it is more efficient to establish an extendable simulation model and make auto-configuration to analyze different kinds of reconfigurable production workspace, rather than construct a simulation model for each scenario. However, it is difficult to automatically configure a simulation model with long programming codes and complex coupled constraints among orders, materials, production machines, and production lines. To solve this problem, this paper establishes a key-value mapping rule to map key and repetitive information and decouple constraints among different parts of simulation model. Then, a chain-of-thought-based model auto-configuration method is proposed to configure a simulation model by using large-language model for programming code generation. To ensure correct and credible simulation model configuration, an automatic evaluation pipeline is also established. Experimental results on a typical extendable Anylogic simulation model for reconfigurable production workshop show that the proposed method can automatically generate appropriate simulation models for different scenarios with high precision greater than 90%.
KW - Chain-of-Thought
KW - Key-Value Mapping Rule
KW - Large Language Model
KW - Prompt Optimization
KW - Simulation Model Auto-Configuration
UR - https://www.scopus.com/pages/publications/105023138557
U2 - 10.1007/978-981-95-4472-1_23
DO - 10.1007/978-981-95-4472-1_23
M3 - 会议稿件
AN - SCOPUS:105023138557
SN - 9789819544714
T3 - Communications in Computer and Information Science
SP - 259
EP - 265
BT - Methods and Applications for Modeling and Simulation of Complex Systems - 24th Asia Simulation Conference, AsiaSim 2025, Proceedings
A2 - Cai, Wentong
A2 - Low, Malcolm
A2 - Tan, Gary
A2 - D'Angelo, Gabriele
A2 - Ta, Duong
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th Asia Simulation Conference on Methods and Applications for Modeling and Simulation of Complex Systems, AsiaSim 2025
Y2 - 17 November 2025 through 19 November 2025
ER -