Network topology design problems find application in several real life scenarios. However, most designs in the past either optimize for a single criterion like delay or assume simplistic traffic models like Poisson. Such assumptions make the solutions inapplicable in the practical world. In this paper, we formulate and solve a multiobjective network topology design problem for a realistic Internet traffic model which is assumed to be self similar. We optimize for the average packet delivery delay and network layout cost to construct realistic network topologies. We present a multiobjective evolutionary algorithm (MOEA) to obtain the diverse near-optimal network topologies. For fair comparison, we design a multiobjective deterministic heuristic based on branch exchange – we call the heuristic Pareto Branch Exchange (PBE). We empirically show that the MOEA used performs well for real networks of various sizes, and generated topologies are quite different with significantly larger delays for the self similar traffic model.

Abstract: Recent research has concentrated on different designs in order to increase the bandwidth of patch antennas and thus improve functionality of wireless communication systems. An alternative approach as shown in this paper is to design a matched probe fed rectangular patch antenna which can operate at both dual frequency (1.9 GHz and 2.4 GHz) and dual polarisation. In this design there are four variables, the two dimensions of the rectangular patch, ‘a ’ and ‘b ’ and position of the probe feed ‘Xp ’ and ‘YP’. As there is not a unique solution Genetic Algorithm (GA) was applied using two objective functions for the return loss at each frequency. The antenna was then modelled using AWR software and the predicted and practical results are shown to be in good agreement. Key Words: Genetic algorithm (GA), dual frequency, dual polarisation, probe fed patch antenna

Genetic Algorithm with Multiobjective formulations are realistic models for many complex engineering optimization problems such as QoS routing protocol for mobile ad hoc network. The paper presents QoS routing protocol for MANET with specialized encoding, initialization, crossovers, mutations, fitness selections and route search using genetic algorithm with multiple objectives. The aim is to find the best QoS route in order to optimize the design of MANET routing protocols. This NP-hard problem is often highly constrained such that random initialization and standard genetic operators usually generate infeasible networks. The performances of the protocol was done to indicate the feasible of the proposed multiobjectives formulation.

This paper addresses the topological optimization problem of interconnection networks where the overall cost of the network is minimized subjected to a predefined network reliability constraint. A new method based on genetic algorithm is proposed which uses more efficient encoding, cross over and mutation rate to ensure a better rate of convergence towards optimal solution. The proposed method is well equipped with some new algorithms for each of the operations stated above with suitable step wise illustration. The minimum cost of fully connected networks with up to 15 numbers of nodes and 105 numbers of links are computed with respect to different targeted values of reliability. Further the optimal layout of the interconnection networks within the above computed cost are presented that meets the network reliability constraints.