Research on Key Technologies of Optimal Routing Design in Ad Hoc Networks

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In this paper, to the deficiencies of the Ad Hoc network in optimization design, we design a multi-objective heuristic algorithm to optimize global collocation of the routing protocol parameters with Pareto genetic algorithm. In process of the optimization, based on the performance indicator value corresponding to individual of the entire group calculate its Pareto Level to obtain a Pareto optimal set, and each solution in the collection is Pareto optimal solution.

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2312-2315

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] D. E. Goldberg. Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley Professional, (1989).

Google Scholar

[2] C. M. Fonseca, P. J. Fleming. Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization. Genetic Algorithms: Proceedings of the Fifth International Conference, 1993: 416-423.

Google Scholar

[3] P. Hajela, C. –Y. Lin. Genetic Search Strategies in Multicriterion Optimal Design. Structural and Multidisciplinary Optimization, 1992, 4(2): 99-107.

DOI: 10.1007/bf01759923

Google Scholar

[4] J. D. Schaffer. Multiple Objective Optimization with Vector Evaluated Genetic Algorithms. Proceedings of the International Conference on Genetic Algorithm and Their Applications, 1985: 93-100.

Google Scholar

[5] D. E. Goldberg, J. Richardson. Genetic Algorithms with Sharing for Multimodal Function Optimization. Genetic Algorithms and Their Applications: Proceedings of the Second International Conference on Genetic Algorithms, 1987: 41-49.

Google Scholar