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
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Computers and Operations Research
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 DE algorithm with a multiple strategy for solving the terminal assignment problem
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Swarm optimisation algorithms applied to large balanced communication networks
Journal of Network and Computer Applications
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Terminal Assignment is an important problem in telecommunication networks. The main objective is to assign a given collection of terminals to a given collection of concentrators. In this paper, we propose a Discrete Differential Evolution (DDE) algorithm for solving the Terminal Assignment problem. Differential Evolution algorithm is an evolutionary computation algorithm. This method has proved to be of practical success in a variety of problem domains. However, it does not perform well on dealing with Terminal Assignment problem because it uses discrete decision variables. To remedy this, a DDE algorithm is proposed to solve this problem. The results are compared to those given by some existing heuristics. We show that the proposed DDE algorithm is able to achieve feasible solutions to Terminal Assignment instances, improving the results obtained by previous approaches.