Terminal assignment in a communications network using genetic algorithms
CSC '94 Proceedings of the 22nd annual ACM computer science conference on Scaling up : meeting the challenge of complexity in real-world computing applications: meeting the challenge of complexity in real-world computing applications
Heuristic algorithms for the terminal assignment problem
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Journal of Global Optimization
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment Problem
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Discrete differential evolution algorithm for solving the terminal assignment problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Swarm optimisation algorithms applied to large balanced communication networks
Journal of Network and Computer Applications
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In the last decades a large amount of interests have been focused on telecommunication network problems One important problem in telecommunication networks is the terminal assignment problem In this paper, we propose a Differential Evolution algorithm employing a “multiple” strategy to solve the Terminal Assignment problem A set of available strategies is established initially In each generation a strategy is selected based on the amount fitness improvements achieved over a number of previous generations We use tournament selection for this purpose Simulation results with the different methods implemented are compared.