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In Internet Routing, the static shortest path (SP) problem has been addressedusing well known intelligent optimization techniques like artificial neuralnetworks, genetic algorithms (GAs) and particle swarm optimization. Advancementin wireless communication lead more and more mobile wireless networks, such asmobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks.Dynamic nature of the network is the main characteristic of MANET. Therefore,the SP routing problem in MANET turns into dynamic optimization problem (DOP).Here the nodes ae made aware of the environmental condition, thereby making itintelligent, which goes as the input for GA. The implementation then uses GAswith immigrants and memory schemes to solve the dynamic SP routing problem(DSPRP) in MANETS. In our paper, once the network topology changes, the optimalsolutions in the new environment can be searched using the new immigrants orthe useful information stored in the memory. Results shows GA with newimmigrants shows better convergence result than GA with memory scheme.

Enhanced Genetic Algorithm approach for Solving Dynamic Shortest Path Routing Problems using Immigrants and Memory Schemes