Multiplayer Battle Game

Multiplayer battle game-inspired optimization algorithms are a novel class of metaheuristics drawing inspiration from the competitive dynamics of popular battle royale games. Research focuses on refining these algorithms, such as the Multiplayer Battle Game Optimizer (MBGO) and its variants, by improving search operators and balancing exploration and exploitation to enhance efficiency and accuracy in solving complex numerical optimization problems. These algorithms show promise in tackling challenging tasks like adversarial robust neural architecture search and various engineering design problems, demonstrating their potential impact across diverse scientific and engineering fields.