Enhancement of coarse-grained parallel genetic algorithm for shortest path routing
L. Venkatesan, P. Sivakumar · 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) · 2013
In general efficient way of routing method is used to transfer the data. This routing problem is solved by using Different types of routing algorithms, here we use Coarse-Grained Parallel GA-Based shortest path algorithm. Time computation is the vital parameter in all routing methods. The very shortest path routing algorithm involves reduce time of the transferring data. Using genetic algorithm we can find an efficient path. This algorithm found by using the nature of the genetic operation. Genetic algorithm is used to change the genes from one sub-population to another sub-population in a proper manner. In this paper discussion is going through both simple genetic algorithm and Parallel genetic algorithm and compares performance of both. Here Migration strategy is used to replace the genes. There are four types of strategies that are used to change the genes. These are: Best replace Worst, Best replace Random, Random replace Random, Random replace Worst, Random replace Random. Among these four types of Strategies worst replace best gives the better performance.