Optimization of Best Path Selection Problem Based on Ant Colony Algorithm in Urban Environment

Urban transportation networks are complex with myriads intersections and destinations. Thus, finding the optimal way is one of the critical issues of traffic management. Thus, an Ant Colony Algorithm (ACA) optimization method was used for the city's path section problem. Ants' foraging behavior inspires the ACA to solve optimization problems. ACA has been applied to the urban transport networks. The case study was researched to show its efficiency in finding the optimum or near-optimum paths. The results indicated that the ACA-based method reduced the journey time of transportation in the city.