When large language model meets optimization

Huang, Sen; Yang, Kaixiang; Qi, Sheng; Wang, Rui

doi:10.1016/j.swevo.2024.101663

Swarm and Evolutionary Computation

2024

DOI: 10.1016/j.swevo.2024.101663

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When large language model meets optimization

Sen Huang,

Kaixiang Yang,

Sheng Qi

et al.

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2024

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Nature-Inspired Intelligent Computing: A Comprehensive Survey

Jiao,

Zhao,

Wang

et al. 2024

Research

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Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms. Over the past decades, these paradigms have revealed effective and flexible solutions to practical and complex problems. This paper summarizes the natural mechanisms of diverse advanced nature-inspired intelligent computing paradigms, which provide valuable lessons for building general-purpose machines capable of adapting to the environment autonomously. According to the natural mechanisms, we classify nature-inspired intelligent computing paradigms into 4 types: evolutionary-based, biological-based, social-cultural-based, and science-based. Moreover, this paper also illustrates the interrelationship between these paradigms and natural mechanisms, as well as their real-world applications, offering a comprehensive algorithmic foundation for mitigating unreasonable metaphors. Finally, based on the detailed analysis of natural mechanisms, the challenges of current nature-inspired paradigms and promising future research directions are presented.

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Nature-Inspired Intelligent Computing: A Comprehensive Survey

Jiao,

Zhao,

Wang

et al. 2024

Research

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When large language model meets optimization

Cited by 1 publication

References 55 publications

Nature-Inspired Intelligent Computing: A Comprehensive Survey

Nature-Inspired Intelligent Computing: A Comprehensive Survey

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