OPRO’s application to the Traveling Salesman Problem (TSP) exemplifies its potential in solving complex optimization tasks. The TSP is a well-known problem in computational mathematics involving a salesman who must visit a set of cities, each once, and return to the origin city, with the goal of minimizing the total journey distance. It’s a problem […]

OPRO (Optimization by PROmpting) revolutionizes the use of Large Language Models (LLMs) by applying their advanced linguistic capabilities to optimization tasks. Unlike traditional approaches that rely on specific algorithms for each optimization problem, OPRO utilizes the extensive training of LLMs on diverse datasets, enabling them to understand and generate human language. This training equips LLMs […]

Optimization by PROmpting (OPRO) marks a groundbreaking advancement in the realm of artificial intelligence (AI). This innovative approach harnesses the power of large language models (LLMs) for solving complex optimization problems. Unlike traditional methods, OPRO integrates the sophisticated processing capabilities of LLMs, enabling a more versatile and effective solution strategy. Its significance is profound in […]