Abstarct: Recent advances in wireless sensor network technologies have created a new field of wearable sensor network applications. Applications that are more towards personal care in the field of health, health and treatment. Today, by installing small sensors on the body or inside the body, it is possible to record and monitor various vital signs and physiological parameters. Also, these sensors are able to transmit their information to a main monitoring center through the wearable wireless network. Routing algorithms in wearable sensor networks must have special characteristics due to the sensitivity of their application and the role of its performance on human health. in a way that maximizes the lifetime of network nodes by reducing energy consumption and increases the reliability of sending packets in the network. It is also very important to be real-time and to have a low delay in sending information. To realize the above features, we will need mexta-heuristic routing methods. In this research, inspired by EMRP evolutionary multistep routing protocol, we have presented a new mexta-heuristic method called multistep routing baxsed on POEMRP pelican optimization method. In this method, various parameters such as remaining energy, distance, energy consumption and packet loss rate are used to select the appropriate parent node and route the packet through this parent node to the well. In order to maximize the operational efficiency of the network, we have set the optimal value of the adjustable coefficients of the routing protocol from the over-heuristic method of Pelican (POA). By simulating the proposed method, we have compared the results with the evolutionary multi-step method and we have shown that the lifetime of the network has increased by using Pelican optimization, and the output of the network has increased during the fixed operation time.