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Genetic Algorithm with Approximation Algorithm Based Initial Population Selection for Shortest Path Routing in Mobile Ad Hoc Networks


Affiliations
1 Computer Science and Engineering Department, KS Rangasamy College of Technology, Tiruchengode-637215, India
2 KS Rangasamy College of Technology, Tiruchengode-637215, India
     

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This paper proposes a new Genetic algorithm with shrink wrap algorithm based initial population selection for the dynamic shortest path routing. Shortest path routing is the basic problem for number of real life problems. Different shortest path optimization problems can be solved by using various approximation algorithms due its computational complexity. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The proposed algorithm shows that the GA and shrink wrap algorithms are best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other soft computing and met heuristics algorithms.

Keywords

Combinatorial Optimization, Dynamic Shortest Path Routing Problem, Genetic Algorithm, Shrink Wrap Algorithm.
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  • Genetic Algorithm with Approximation Algorithm Based Initial Population Selection for Shortest Path Routing in Mobile Ad Hoc Networks

Abstract Views: 211  |  PDF Views: 3

Authors

R. Nallusamy
Computer Science and Engineering Department, KS Rangasamy College of Technology, Tiruchengode-637215, India
K. Duraiswamy
KS Rangasamy College of Technology, Tiruchengode-637215, India

Abstract


This paper proposes a new Genetic algorithm with shrink wrap algorithm based initial population selection for the dynamic shortest path routing. Shortest path routing is the basic problem for number of real life problems. Different shortest path optimization problems can be solved by using various approximation algorithms due its computational complexity. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The proposed algorithm shows that the GA and shrink wrap algorithms are best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other soft computing and met heuristics algorithms.

Keywords


Combinatorial Optimization, Dynamic Shortest Path Routing Problem, Genetic Algorithm, Shrink Wrap Algorithm.