Optimization Task

Optimization tasks, aiming to find the best solution among many possibilities, are central to numerous scientific and engineering fields. Current research focuses on improving efficiency and effectiveness across diverse problem types, including large-scale problems with shared variables, multi-objective scenarios, and those involving expensive-to-evaluate functions. Prominent approaches involve advanced algorithms like cooperative coevolution, Bayesian optimization with adaptive acquisition functions, and the novel application of large language models as optimizers. These advancements are impacting various domains, from resource allocation in energy production to robotics and machine learning, by enabling more efficient and robust solutions to complex problems.