Basin Hopping is a competitive option for global optimization, especially in complex problems.
Introducing a novel animal-inspired metaheuristic algorithm, ZSO, designed using a large language model and the CRISPE framework.
Water-based metaheuristics offer unique solutions to NP-hard problems by emulating water dynamics.
The author presents a novel approach to solving the Close Enough Orienteering Problem by leveraging overlapped neighborhoods and introducing non-uniform cost considerations, resulting in efficient solutions.