Abstract: Artificial physics optimization (APO) algorithm is a novel intelligent algorithm that based on physical laws and developed in recent years. This paper describes the basic principle of its calculation and presents a universal heuristic strategy for intelligent algorithms to solve optimal reservoir flood regulating models. In an effort to improve its virtual gravity parameters using the adaptive approach, we have developed an adaptive artificial physics optimization (AAPO) algorithm, expecting to improve its standard searching process. This AAPO algorithm was used to solve the optimal model of real-time flood regulation in operating the Nianyushan reservoir, with the average and variance of its optimal process used for evaluation of its accuracy and stability. In this calculation, the optimal outflow hydrograph of the reservoir was divided into two parts, and each part was calculated separately using a fluctuation ratio indicator to evaluate the feasibility of the new algorithm, along with an indicator of CPU cost. Results show that AAPO is more accurate and more stable than APO and fluctuations in the reservoir outflows optimized by AAPO or APO were weaker than those of other algorithms, indicating its superiority in real-time flood regulation.