The advancement in wireless communications has become more and more mobile wireless networks. The most essential feature in mobile ad hoc networks is topology change i.e., the topology of the network changes over time to time since node mobility occurs often. Therefore finding the shortest path for the routing problem in Mobile Adhoc NETworks (MANETs) will become a dynamic optimization problem. Using a Genetic Algorithm with immigrants and memory schemes to solve the dynamic Shortest Path routing problem in MANETs cannot achieve global optimization. Using PSO (Particle Swarm Optimization) and BFO (Bacterial Foraging Optimization) algorithmic techniques can achieve the global optimum of a realvalued function (fitness function) defined in a given space (search space).