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From natural language to simulations: applying AI to automate simulation modelling of logistics systems.

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Název: From natural language to simulations: applying AI to automate simulation modelling of logistics systems.
Autoři: Jackson, Ilya, Jesus Saenz, Maria, Ivanov, Dmitry
Zdroj: International Journal of Production Research; Feb2024, Vol. 62 Issue 4, p1434-1457, 24p
Témata: LANGUAGE models, INVENTORY management systems, NATURAL languages, SIMULATION methods & models, GENERATIVE artificial intelligence, ARTIFICIAL intelligence
Abstrakt: Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and how human experts and artificial intelligence (AI)-based systems can collaborate in the domain of simulation modelling. We demonstrate that a framework constructed upon the refined GPT-3 Codex is capable of generating functionally valid simulations for queuing and inventory management systems when provided with a verbal explanation. As a result, the language model could produce simulation models for inventory and process control. These results, along with the rapid improvement of language models, enable a significant simplification of simulation model development. Our study offers guidelines and a design of a natural language processing-based framework on how to build simulation models of logistics systems automatically, given the verbal description. In generalised terms, our work offers a technological underpinning of human-AI collaboration for the development of simulation models. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt:Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and how human experts and artificial intelligence (AI)-based systems can collaborate in the domain of simulation modelling. We demonstrate that a framework constructed upon the refined GPT-3 Codex is capable of generating functionally valid simulations for queuing and inventory management systems when provided with a verbal explanation. As a result, the language model could produce simulation models for inventory and process control. These results, along with the rapid improvement of language models, enable a significant simplification of simulation model development. Our study offers guidelines and a design of a natural language processing-based framework on how to build simulation models of logistics systems automatically, given the verbal description. In generalised terms, our work offers a technological underpinning of human-AI collaboration for the development of simulation models. [ABSTRACT FROM AUTHOR]
ISSN:00207543
DOI:10.1080/00207543.2023.2276811