Abstract

The present paper deals with the economic optimization of a series of 15 bridge piers with rectangular hollow sections. It combines height columns of 20, 30, 40, 50 and 60 m and viaducts of 40, 50 and 60 m of main intermediate spans. The optimization uses a variant of the ant colony method. Results show the variation in geometry, concrete quality, reinforcement and cost, both in the footings and in the main column, as the columns gain height and the viaducts grow in span length.

Abstract

International audience; In this paper, ant colony optimization algorithm (ACOA) is proposed to solve the problem of how to efficiently operate a natural gas pipeline under steady state assumptions. The system is composed by compressing stations linked by pipe-legs. For each station, it is necessary to find the operating turbocompressors optimal values and the discharge pressures ones to minimize the total amount of fuel gas consumed in the system by the compressor stations. In the past, several techniques ranging from classical gradient-based procedures to dynamic programming, for solving this no convex problem have been applied. In this paper, we propose the ant colony optimization metaheuristic. This method was applied to the gas pipeline Hassi R' mell- ARZEW (two cities in Algeria) and the results are compared with those obtained by employing dynamic programming method. From these results, we obtain that the ACO technique is an interesting way for the gas pipeline operations optimization.

Abstract

To meet the demanded bandwidth requirements of future optical communication networks, more dynamism, scalability and automatism will need to be provided, which will require, as well, new control plane designs to respond to network changes very rapidly. In this work, we propose the use of an ant colony optimization (ACO) algorithm to support the routing and wavelength assignment in wavelength continuity constraint optical burst-switched networks. The main advantage of the protocol is its distributed nature, which provides higher survivability to network failures or traffic congestion. From the results we see that the new protocol responds effectively to congestion while at the same time providing better performance in comparison to the shortest path routing with random wavelength assignment. Peer Reviewed

Abstract

International audience; The constant increase in air traffic, since the beginning of the commercial aviation, has led to problems of saturation on airports, approaching areas,or higher airspace.Whereas the aircraft are largely optimized and automated, the air traffic control is still essentially relying on human experience.The present case study details two problems of air traffic management (ATM) for which a genetic algorithm based solution has been proposed. Thefirst application deals with the en route conflict resolution problem. The second application deals with the traffic management problem in an airport platform.

Abstract

International audience; In this paper, we introduce an Ant Colony System algorithm which finds optimal or near-optimal sequences of airspace partitions, taking into account some constraints on the transitions between two successive airspace configurations. The transitions should be simple enough to allow air traffic controllers to maintain their situation awareness during the airspace configuration changes. For the same reason, once a sector is opened it should remain so for a minimum duration. The Ant Colony System (ACS) finds a sequence of airspace configurations minimizing a cost related to the workload and the usage of manpower resources, while satisfying the transition constraints. This approach shows good results in a limited time when compared with a previously proposed $A$ * algorithm on some instances from the french air traffic control center of Aix (East qualification zone) where the $A$ * algorithm exhibited high computation times.00