We consider networks where mobile sensor/actor nodes move to specific locations in order to conduct data collection or deliver a response to an event. The challenge is to find the best tour for the mobile nodes in order to visit the given set of locations. In this paper, the objective of the optimization is to extend the node lifetime by emphasizing both path efficiency and balanced energy consumption when identifying and assigning tours to mobile nodes. Compared to existing schemes in the literature, we consider the initial position of mobile sensors when determining the tours. We formulate the optimization as a balanced multi-salesman travel problem and propose a solution based on a two-step approach. First, we determine the shortest tour that includes all event locations by forming the Hamiltonian cycle. Then, we formulate the optimal partitioning of such a cycle as a linear program (LP) where the objective is to reduce the tour length while minimizing the maximum tour a node has to be make. For scalability and to expedite convergence, we propose a method for solving the LP formulation based on Branch & Price algorithm. The simulation results confirm the effectiveness of our optimization formulation and the advantage of our solution compared to competing schemes.