Internet of Things (IoT) is a promising technology that enables interconnecting billions of electronic devices over communication networks. Multicasting is an essential service in IoT which allows the IoT devices to disseminate common messages more efficiently. Energy consumption is one of the main concerns in designing and implementing IoT since the IoT devices are expected to run for long periods of time using batteries in general. Moreover, IoT devices that participate in forwarding multicast messages excessively may deplete their energy sooner than expected. In this paper, we proposed to employ Radio Frequency (RF) energy harvesting technology with the IoT device in order to wirelessly power multicast sessions. Each IoT device that forwards a multicast message is compensated for the energy consumed for transmission by energy transmitted from Energy Transmitters (ETs). We formulate an optimal operational strategy, where the objective is to minimize the total transmitted energy from the ETs. The problem is in the form of non-convex Mixed Integer Nonlinear Problem, where there is no efficient way to solve the problem optimally when the number of variables is relatively large. Therefore, we first approximate the data rate function with a concave lower bound function. Then, we decompose the optimization problem using Generalized Bender Decomposition (GBD) into: 1) Convex Nonlinear Program (NLP) and 2) Mixed Integer Linear Program (MILP). Moreover, we employ Successive Convex Programming (SCP) within GBD algorithm to iteratively find a better approximation for the original problem. Our simula- tion results show that GBD-SCP algorithm solves the optimization problem more efficiently with a performance close to optimal.