Advanced multi-objective evolutionary algorithms applied to two problems in telecommunications

Most research in optimisation is aimed at single objective problems, where the aim is to find a solution which maximises or minimises a single quality measure. However, as in minor, many problems in telecommunications are fundamentally multy-objective, particularly where the issues involved are related to quality of service, or cost/reliability trade-offs. There has been considerable research in multi-objective optimisation, but, until recently, the most prominently known multi-objective optimisation algorithms have tended to be rather slow, and there has been no universidly accepted way to properly compare the performance of different methods. Here, we describe two evolutionary computation-based multy-objective optimisation methods which have recently been shown both to be considerably faster than the classical set of such methods, and to outperform existing methods on a wide range of test problems. We focus on two application areas in telecommunications the adaptive distributed database management problem, and the offline-routeing problem. The speed and quality of these new methods suggest that their adoption in live applications of these and other telecommunications-related problems is feasible.