In order to solve the problem that the unbalanced positional distribution of randomly screened cluster head nodes and unreasonable data transmission paths of forwarding nodes of the cluster routing protocol for wireless sensor networks will exacerbate the node's energy consumption and shorten the network's survival period, a multifactorial balanced dynamic cluster routing protocol based on improved social network search (ISNS) algorithm optimized fuzzy C-mean clustering (FCM) (multi-factor balanced dynamic clustering routing protocol, MD-LEACH) was proposed. Firstly, the Levy flight was introduced to improve the reverse elite learning strategy to enhance the global optimization capability of the social network search algorithm. Then, the ISNS-optimized fuzzy C-mean clustering algorithm was used to dynamically cluster the network nodes uniformly and balance the load of the network. Moreover, fuzzy reasoning was introduced to consider the energy factor and the location factor of nodes in the clusters in each cluster, and two cluster-head selection modes were designed to dynamically elect the cluster head to improve the Cluster head quality. In the stable transmission phase, the single hop was changed to the way of communication between cluster heads, and the improved ant colony algorithm was used to find the optimal data transmission path to improve the energy efficiency. Simulation results show that the algorithm can effectively improve the energy efficiency, balance the network load, and extend the network survival period.