Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Comparison of Algorithms for the Degree Constrained Minimum Spanning Tree
Journal of Heuristics
A New Genetic Algorithm for the Optimal Communication Spanning Tree Problem
AE '99 Selected Papers from the 4th European Conference on Artificial Evolution
QoS Multicast Routing in Networks with Uncertain Parameters
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Explicit Multicast Routing Algorithms for Constrained Traffic Engineering
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
A Multiobjective Model for QoS Multicast Routing Based on Genetic Algorithm
ICCNMC '03 Proceedings of the 2003 International Conference on Computer Networks and Mobile Computing
A GA-based Multi-purpose Optimization Algorithm for QoS Routing
AINA '04 Proceedings of the 18th International Conference on Advanced Information Networking and Applications - Volume 2
Multi-objective scheme over multi-tree routing in multicast MPLS networks
LANC '03 Proceedings of the 2003 IFIP/ACM Latin America conference on Towards a Latin American agenda for network research
A genetic algorithm for the multiple destination routing problems
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
QoS routing based on genetic algorithm
Computer Communications
Optimizing OSPF/IS-IS weights in a changing world
IEEE Journal on Selected Areas in Communications
Applying genetic algorithms to decision making in autonomic computing systems
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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This paper presents a new traffic engineering load balancing taxonomy, classifying several publications and including their objective functions, constraints and proposed heuristics. Using this classification, a novel Generalized Multiobjective Multitree model (GMM-model) is proposed. This model considers for the first time multitree-multicast load balancing with splitting in a multiobjective context, whose mathematical solution is a whole Pareto optimal set that can include several results than it has been possible to find in the publications surveyed. To solve the GMM-model, a multi-objective evolutionary algorithm (MOEA) inspired by the Strength Pareto Evolutionary Algorithm (SPEA) is proposed. Experimental results considering up to 11 different objectives are presented for the well-known NSF network, with two simultaneous data flows.