We propose and demonstrate a new methodology to stabilize systems with complex dynamics like the supply chain. This method is based on the accumulated deviations from equilibrium (ADE). It is most beneficial for controlling system dynamic models characterized by multiple types of delays, many interacting variables, and feedback processes. We employ the classical version of particle swarm optimization as the optimization approach due to its performance in multidimensional space, stochastic properties, and global reach. We demonstrate the effectiveness of our method based on ADE using a manufacturing‐supply‐chain case study.