Dolphins are highly social marine mammals, and their group behavior exhibits characteristics such as collaborative hunting, information sharing, and dynamic role allocation. Inspired by dolphin pod behavior, this paper proposes a new swarm intelligence optimization algorithm, called Dolphin Pod Optimization (DPO). This algorithm incorporates acoustic cooperative navigation, pod energy regulation, and dynamic role allocation to achieve efficient movement of individuals within the search space. This paper provides a detailed derivation of the algorithm's mathematical model and presents mathematical formulas in plain text format to facilitate theoretical analysis and subsequent improvements. The algorithm's characteristics include adaptive exploration and exploitation balance, pod collaborative optimization, and enhanced global search capabilities. This paper provides a new theoretical framework and methodology for swarm intelligence optimization algorithms.