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Ant Colony Optimization (ACO) meta-heuristic, a subset of swarm intelligence, is an inherently parallelizable search technique recently proposed to determine routing in ad hoc networks. One of the many interesting features of swarm based approach is their ability to solve problems that are not static but are spatially distributed and changing over time. In this paper we report our experiences in design, development and implementation of a parallel algorithm for mobile ad hoc networks (MANETs) using the ACO technique on a shared memory architecture with OpenMP. We have experimented with three scheduling policies provided by OpenMP for varying data sizes. Also we report comparison of the performance results with message passing environment (MPI).