A Hybrid Ant Colony Optimization Algorithm for Network Routing and Planning
نویسندگان
چکیده
The mechanism of route search problem is applied to various engineering fields. The various researches for the dynamic routing only revile the shortest path from source to destination but not vice versa. Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behavior is avoided. Several approaches have been integrated with ACO to improve its performance for DOPs. The main objective of this work is to search out the least-time-cost route in a variable-edge-weight graph. It can find multiple transmission paths from sources to the goal by parallel search. We introduce time-dependent pheromones and feedback path model as two heuristic factors to improve the basic ACO. Finally, this proposed heuristic algorithm is verified to be steady-going by repeated testing [1]. Ant Colony Optimization Technique has been applied in different network models with different number of nodes and structure to find the shortest path with optimum throughput. The simulation results show that the proposed dynamic ACO algorithm can effectively reduce time cost by avoiding the dynamic congestion areas. The experimental results show that the algorithm is more effective than the existing ones and it improves the Quality of Service (QoS) [13[14][15]. General Terms: Route Optimization, Shortest path, Real-
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