Deep Sea Jellyfish Optimization Algorithm

The Deep Sea Jellyfish Optimization Algorithm (DSJOA) is a novel swarm optimization algorithm. Based on the floating, predation, and cooperative behaviors of deep-sea jellyfish, it simulates their movement and foraging behavior in the deep-sea environment to achieve optimization search. Compared with traditional swarm optimization algorithms, DSJOA has significant advantages in global search capability, local exploitation capability, and adaptability to complex and dynamic optimization problems. This paper systematically elaborates on DSJOA from the aspects of algorithm modeling, mathematical mechanism, iterative process, and characteristic analysis, providing an effective new method for solving high-dimensional continuous optimization problems, constrained optimization problems, and dynamic optimization problems.