Speeding up of genetic algorithm for network topology optimization with use of cumulative updating of network reliability
Network optimization problems in conditions of constraints are NP-hard problems mostly. Genetic Algorithms are applicable solution for network structure optimization and for obtaining good results within acceptable periods of time. In this study we consider the problem of network topology optimization with unreliable communication channels and perfectly reliable nodes in order to obtain the most reliable structure. The problem of reliability computing for such networks is NP-hard so exact algorithm demands enormous computational effort. However, the method based on cumulative updating of lower and upper bounds of network reliability allows to decide the feasibility of a given network without performing exhaustive calculation of reliability. Relying on this technique we propose a new method which speed up network optimization process by the genetic algorithm.