Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm

In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.

Ant-Colony Optimization for the System Reliability Problem with Quantity Discounts

This research presents an approach based upon ant-colony optimization to address the system reliability problem. For each component of a system, the number of units in parallel needs to be chosen to maximize the reliability for the entire system. As more parallel units are selected, costs increase in a proportional fashion. For this effort, quantity discounts for additional parallel units are considered, and the budget for purchase of parallel units is limited. Ant colony optimization methodology is employed to find an optimal system reliability that satisfies the budget constraint. The methodology is employed for several test problems, and near-optimal solutions are found.

A cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks

In order to periodically reassess the status of the alternate path route(APR)set and to improve the efficiency of alternate path construction existing in most current alter-nate path routing protocols,we present a cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks(CALRA)in this paper.In CALRA,the APR set maintained in nodes is aged and reas-sessed by the inherent mechanism of pheromone evaporation of ant-colony optimization algorithm,and load balance of network is achieved by ant-colony optimization combining with cross-layer synthetic optimization.The efficiency of APR set construction is improved by bidirectional and hop-by-hop routing update during routing discovery and routing maintenance process.Moreover,ants in CALRA deposit simulated pheromones as a function of multiple parameters corresponding to the information collected by each layer of each node visited,such as the distance from their source node,the congestion degree of the visited nodes,the current pheromones the nodes possess,the velocity of the nodes,and so on,and provide the information to the visiting nodes to update their pheromone tables by endowing the different parameters corresponding to different information and different weight values,which provides a new method to improve the congestion problem,the shortcut problem,the convergence rate and the heavy overheads commonly existed in existing ant-based routing protocols for ad-hoc networks.The performance of the algorithm is measured by the packet delivery rate,good-put ratio(routing overhead),and end-to-end delay.Simulation results show that CALRA performs well in decreasing the route overheads,balancing traffic load,as well as increasing the packet delivery rate,etc.