This article reports the results of mixed convection heat transfer studies from five heat sources (aluminum) mounted at different positions on a substrate board (Bakelite). The goal is to determine the optimal arrangement, such that, the maximum temperature excess is minimum among all the possible configurations. For accomplishing this, a completely experimental driven hybrid optimization strategy, that combines Artificial neural network (ANN) with Genetic algorithm (GA) is used. Initial optimization studies are carried out by employing a heuristic non-dimensional geometric parameter lambda, which is identified to be the key parameter to decide the maximum temperature in the system.