Ant colony optimization phd thesis

Ant colony optimization phd thesis

Training feed-forward neural networks with ant colony optimization: An application to pattern classification. In Hybrid Intelligent Systems, HIS’ Fifth International Conference on, pages 6–pp. IEEE, 4. A. Pandian. Training neural networks with ant colony optimization. PhD thesis, California State University, Sacramento, 5. M Ant Colony Optimization Phd Thesis We want to share a special discount with you on your first purchase. Please leave your email, and we’ll send you a 10% OFF coupon with an exclusive promo code. Use it when placing your order and discover all the Ant Colony Optimization Phd Thesis benefits of our company Ant Colony Optimization Phd Thesis, Thesis Group Acknowledgement, Cover Letter For Nih Grant Sample, 7the Grade Informative Essay Projects. We accept. Quality level. Reviews: 4%. SUBMIT NOW. Follow us. 24/7 CUSTOMER SUPPORT» Accounting Dissertation

For large and dynamic networks, traditional MANETs multicast routing protocols are not appropriate for searching the optimal paths considering QoS constraints as the problem leads to NP-complete in nature. Biologically inspired algorithms like Ant colony optimization ACOParticle swarm optimization PSO and Artificial Bee Colony have attracted great attention from researchers to solve the combinatorial problem. ACO and PSO provide more reliable routes as compared to traditional methods.

In this paper, we have proposed 'Hybrid ACO-PSO Meta-Heuristic HAPM ', a combination of ACO, PSO, and a dynamic ant colony optimization phd thesis mechanism to improve QoS constraints and minimize QoS the data dropping. Simulation is performed in NS2 and the ant colony optimization phd thesis revealed that the presented HAPM algorithm provides better efficiency in terms of Packet Delivery Ratio PDRant colony optimization phd thesis, Ent-to-End Delay, Hop Count H cRouting Overhead and Throughput as compared to ACO, PSO, hybrid ACO-PSO, Enhanced-Ant-AODV and Cuckoo Search Optimization AODV CSO-AODV.

The proposed HAPM does not overburden the time complexity in our implementation. This is a preview of subscription content, access via your institution. Rent this article via DeepDyve. Sahasrabuddhe, L. Multicast routing algorithms and protocols: A tutorial.

IEEE Network, 14 190— Article Google Scholar. Perkins, C. RFC Ad hoc on-demand distance vector AODV routing. Highly dynamic destination-sequenced distance-vector routing DSDV for mobile computers.

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International Journal of Engineering and Advanced Technology IJEAT8 5— Gupta, M. Performance evaluation of DSR, AODV and DSDV routing protocol for wireless Adhoc network. In: IEEE International Conference on Computational Intelligence and Communication TechnologyIEEE, pp. Sahana, Ant colony optimization phd thesis. Hybrid optimizer for the travelling salesman problem. Evolutionary Intelligence, 12 2— Radha, S. Performance evaluation of routing algorithms for mobility models in ad hoc network.

IETE Technical Review, 21 3— QoS-based ACO routing protocols in MANETs: A review. In: Proceedings of the Fourth International Conference on Microelectronics Computing and Communication SystemsSpringer, Singapore, pp.

An efficient swarm-based multicast routing technique: Review. In Computational Intelligence in Data Miningpp. Memon, ant colony optimization phd thesis, S.

Performance evaluation of mobile ad hoc routing mechanisms. Wireless Personal Communications, 85 2— Dorigo, M. Optimization, learning and natural algorithms. PhD Thesis, Politecnico di Milano. Eberhart, R. A new optimizer using particle swarm theory. In: MHS' Proceedings of the Sixth International Symposium on Micro Machine and Human ScienceIEEE, pp. In: Proceedings of the Congress on Evolutionary Computation-CEC99 Cat.

Gunes, M. In Proceedings. International Conference on Parallel Processing WorkshopIEEE, pp. Hussein, O. Ant routing algorithm for mobile ad-hoc networks ARAMA. In: Conference Proceedings of the IEEE International Performance, ant colony optimization phd thesis, Computing, and Communications Conference,IEEE, pp. Di Caro, G. AntHocNet: An adaptive nature-inspired algorithm for routing in mobile ad hoc networks.

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International Journal of Computer Science and Security, 2 348— Osagie, E. PACONET: imProved ant colony optimization routing algorithm for mobile ad hoc networks, ant colony optimization phd thesis. In 22nd International Conference on Advanced Information Networking and Applications ainaIEEE, pp.

Wang, J. HOPNET: A hybrid ant colony optimization routing algorithm for mobile ad hoc network. Ad Hoc Networks, 7 4— Deepalakshmi, P. An ant colony-based multi objective quality of service routing for mobile ad hoc networks. EURASIP Journal on Wireless Communications and Networking,1— Krishna, P. Quality-of-service-enabled ant colony-based multipath routing for mobile ad hoc networks. IET Communications, 6 176— MathSciNet Article Google Scholar.

Al-Ani, A. QoS-aware routing in multi-rate ad hoc networks based on ant colony optimization. Network Protocols and Algorithms, 7 41— Wang, Z. A PSO-based multicast routing algorithm. In: Third International Conference on Natural Computation ICNCIEEE, vol. Patel, M. Ain Shams Engineering Journal, 5 1— Girgis, M. Tree growth based ACO algorithm for solving the bandwidth-delay-constrained least-cost multicast routing problem. International Journal of Computer and Information Technology, 5 6— Harrag, N.

Bio-inspired OLSR routing protocol. Mandhare, V. QoS routing enhancement using metaheuristic approach ant colony optimization phd thesis mobile ad-hoc network. Computer Networks,— Sarkar, D. Enhanced-ant-AODV for optimal route selection in mobile ad-hoc network. Journal of King Saud University-Computer and Information Sciences. Download references.

What is the Ant Colony Optimization Algorithm?

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Ant Colony Optimization Phd Thesis, Thesis Group Acknowledgement, Cover Letter For Nih Grant Sample, 7the Grade Informative Essay Projects. We accept. Quality level. Reviews: 4%. SUBMIT NOW. Follow us. 24/7 CUSTOMER SUPPORT» Accounting Dissertation Such is the case in design of many types of roads, pipelines, and utilities. This thesis proposes a multi-objective ant colony optimization algorithm capable of producing solutions to infrastructure routing problems with more than one objective. Ant Colony Optimization was first proposed by Marco Dorigo in his PhD work The newly produced bacteria occupy position of Ant Colony Optimization (ACO) eliminated bacteria. The bacteria with best fitness value, that In , Marco Dorigo [24] proposed a new algorithm in his is, minimum cost finally represent the solution to an objective PhD thesis, Ant colony optimization