Multi-Objective Routing Optimization Using Evolutionary Algorithms

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Wireless ad hoc networks suffer from several limitations, such as routing failures, potentially excessive bandwidth requirements, computational constraints and limited storage capability. Their routing strategy plays a significant role in determining the overall performance of the multi-hop network. However, in conventional network design only one of the desired routing-related objectives is optimized, while other objectives are typically assumed to be the constraints imposed on the problem. In this paper, the authors invoke the Non-dominated Sorting based Genetic Algorithm-II (NSGA-II) and the Multi-Objective Differential Evolution (MODE) algorithm for finding optimal routes from a given source to a given destination in the face of conflicting design objectives, such as the dissipated energy and the end-to-end delay in a fully connected arbitrary multi-hop network.