A neural network technique known as Kohonen unsupervised training is coupled with a modified version of the particle swarm optimization technique in an effort to develop an algorithm capable of finding multiple optimal solutions for a given problem. The ability to find multiple optimal solutions is of interest in many different applications, such as complex engineering design problems, where it's beneficial to analyze more than one potential design or solution. The results of five example problems of increasing difficulty validate the Alternative Analysis Networking algorithm's functionality. This algorithm is an efficient and robust technique, and appears to be the first capable of performing the task of finding multiple optimal solutions as efficiently as typical stochastic-based optimizers.