Year: 2024
Type: article
Abstract: In this letter, we present the Large Language Model-based combinatorial optimizer (LMCO) for wireless network optimization and planning tasks, focusing on optimizing the number and the placement of wireless access point placement. The performance and efficiency of LMCO are evaluated and compared with the well-established Ant Colony Optimization (ACO) algorithm. The results indicate that LMCO exhibits superior performance, particularly as the complexity of the problem increases. These findings also underscore the significant potential of LLM-based algorithms in revolutionizing combinatorial optimization across a wide range of applications.
Institutions: University of Cambridge, Brunel University of London
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G3950210789, G4384862669
OpenAlex ID: W4402570079
