In this study, two developed shortest path algorithms that run fast on the real large volume road networks have been identified. The first one is heuristic genetic algorithm implemented with approximate buckets in scalar computing environment and the second one is parallel genetic processing which is run in the alternative space. At first, these two algorithms were reviewed and summarized and their data structures and procedures are presented. Continually, in this effort genetic algorithm is used to solve the shortest path problem, because the limitation of traditional optimization methods. Finally, present result demonstrates that parallel heuristic processing can produce better speed up performance for real-time transportation applications

Keywords