Markov Chain Models for Genetic Algorithm Based Topology Control in MANETs

Author:

Şahin Cem Şafak,Gundry Stephen,Urrea Elkin,Uyar M. Ümit,Conner Michael,Bertoli Giorgio,Pizzo Christian

Publisher

Springer Berlin Heidelberg

Reference18 articles.

1. Eiben, A.E., Aarts, E., Hee, K.M.: Global convergence of genetic algorithms: A markov chain analysis. In: PPSN I: Proceedings of the 1st Workshop on Parallel Problem Solving from Nature, pp. 4–12. Springer, London (1991)

2. Khosraviani, M., Pour-Mozafari, S., Ebadzadeh, M.M.: Convergence analysis of quantum-inspired genetic algorithms with the population of a single individual. In: GECCO 2008: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pp. 1115–1116. ACM, New York (2008)

3. Sahin, C.S., Urrea, U., Uyar, M.U., Conner, M., Hokelek, I., Bertoli, G., Pizzo, C.: Genetic algorithms for self-spreading nodes in manets. In: GECCO 2008: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pp. 1115–1116. ACM, New York (2008)

4. Sahin, C.S., Urrea, E., Uyar, M.U., Conner, M., Bertoli, G., Pizzo, C.: Design of genetic algorithms for topology control of unmanned vehicles. Special Issue of the Int. J. of Applied Decision Sciences on Decision Support Systems for Unmanned Vehicles (2010) (accepted)

5. Chiang, T., Liu, C., Huang, Y.: A near-optimal multicast scheme for mobile ad hoc networks using a hybrid genetic algorithm. Expert Syst. Appl. 33(3), 734–742 (2007)

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