Numerical recipes in C: the art of scientific computing
Numerical recipes in C: the art of scientific computing
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Computer networks (3rd ed.)
ATM networks: principles and use
ATM networks: principles and use
Memetic algorithms: a short introduction
New ideas in optimization
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Telecommunications Optimization: Heuristic and Adaptive Computation Techniques
Telecommunications Optimization: Heuristic and Adaptive Computation Techniques
On the Performance Assessment and Comparison of Stochastic Multiobjective Optimizers
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
On set-based multiobjective optimization
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Nature-Inspired Computing Technology and Applications
BT Technology Journal
Computer Networks: The International Journal of Computer and Telecommunications Networking
Multiobjective network topology design
Applied Soft Computing
Optimisation of CDMA-based mobile telephone networks: algorithmic studies on real-world networks
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
An end-to-end qos provisioning architecture in IPv6 networks
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
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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 nature, many problems in telecommunications are fundamentally multi-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 universally accepted way to properly compare the performance of different methods. Here, we describe two evolutionary computation-based multi-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.