Abstract Mobile Ad Hoc network (MANET) is a self-organizing and battery constrained network. The design of energy efficient routing has been an active research area. In conventional routing algorithms, the node positioning is varying with time, constrained energy does not ensure route firmness. Moreover, with node movement it becomes very hard to predict and ensuring significant data delivery in MANET is another major concern. To resolve these issues, this paper proposes an energy efficient routing depends on node positioning and Learning Automaton for MANET. Initially, a node firmness model is constructed and on that basis, reward and penalty function are designed according to optimal or non-optimal route identification. A node positioned energy efficient mechanism is constructed for election of accessible routes and manifests convergence of Node Positioned Learning Automaton Energy-efficient Routing algorithm. Next, with the identified energy-efficient optimal route, node with minimal load is selected by employing Statistically-evaluated Load balancing algorithm. Here, statistical means of standard deviation is applied to identify node with minimal load, therefore ensuring higher packet delivery ratio. Finally, with the minimal load evolving node, before performing actual data delivery, transmission probability of the node is ensured by means of Multilateration function. The Multilateration function uses the position information and with this the source node selects the relay nodes that are closer, therefore minimizing packet loss rate. The performance of the proposed Node Positioned Learning Automaton and Multilateration Data Delivery (NPLA-MDD) for MANET is evaluated using energy consumption, packet loss rate and PDR. The results of proposed method outperform than the conventional data delivery methods.