Training recurrent neural networks by using parallel tabu search algorithm based on crossover operation

[1]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[2]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[3]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[4]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[5]  Fred W. Glover,et al.  Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..

[6]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[7]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  Miroslaw Malek,et al.  Serial and parallel simulated annealing and tabu search algorithms for the traveling salesman problem , 1990 .

[10]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[11]  Jeffrey L. Elman,et al.  Finding Structure in Time , 1990, Cogn. Sci..

[12]  Fred Glover,et al.  Tabu search methods for a single machine scheduling problem , 1991, J. Intell. Manuf..

[13]  David Abramson,et al.  Constructing school timetables using simulated annealing: sequential and parallel algorithms , 1991 .

[14]  N. Hu Tabu search method with random moves for globally optimal design , 1992 .

[15]  D. Costa,et al.  A tabu search algorithm for computing an operational timetable , 1994 .

[16]  J. A. Bland A derivative-free exploratory tool for function minimisation based on tabu search , 1994 .

[17]  Jacek Klinowski,et al.  Taboo Search: An Approach to the Multiple Minima Problem , 1995, Science.

[18]  Roberto Battiti,et al.  Training neural nets with the reactive tabu search , 1995, IEEE Trans. Neural Networks.

[19]  D. Karaboga,et al.  Tuning PID controller parameters using tabu search algorithm , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).

[20]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[21]  Roberto Battiti,et al.  The continuous reactive tabu search: Blending combinatorial optimization and stochastic search for global optimization , 1996, Ann. Oper. Res..

[22]  Luca Maria Gambardella,et al.  HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem , 1997 .

[23]  P. Siarry,et al.  FITTING OF TABU SEARCH TO OPTIMIZE FUNCTIONS OF CONTINUOUS VARIABLES , 1997 .

[24]  Bahram Alidaee,et al.  Global optimization for artificial neural networks: A tabu search application , 1998, Eur. J. Oper. Res..

[25]  Marco Dorigo,et al.  Mobile agents for adaptive routing , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[26]  Yang Shiyou,et al.  A universal tabu search algorithm for global optimization of multimodal functions with continuous variables in electromagnetics , 1998 .

[27]  Celso C. Ribeiro,et al.  Cooperative Mult-thread Parallel Tabu Search with an Application to Circuit Partitioning , 1998, IRREGULAR.

[28]  É. Taillard,et al.  MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows , 1999 .

[29]  Duc Truong Pham,et al.  Training Elman and Jordan networks for system identification using genetic algorithms , 1999, Artif. Intell. Eng..

[30]  Chia-Ju Wu,et al.  Design of fuzzy logic controllers using genetic algorithms , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[31]  Riccardo Poli,et al.  New ideas in optimization , 1999 .

[32]  M. Marchesi,et al.  Tabu search metaheuristics for electromagnetic problems optimization in continuous domains , 1999 .

[33]  Wan-Chi Siu,et al.  Adding learning to cellular genetic algorithms for training recurrent neural networks , 1999, IEEE Trans. Neural Networks.

[34]  Jatinder N. D. Gupta,et al.  Comparative evaluation of genetic algorithm and backpropagation for training neural networks , 2000, Inf. Sci..

[35]  Armando Blanco,et al.  A genetic algorithm to obtain the optimal recurrent neural network , 2000, Int. J. Approx. Reason..

[36]  Patrick Siarry,et al.  Tabu Search applied to global optimization , 2000, Eur. J. Oper. Res..

[37]  Juan Julián Merelo Guervós,et al.  G-Prop: Global optimization of multilayer perceptrons using GAs , 2000, Neurocomputing.

[38]  A. Uncini,et al.  Power-of-two adaptive filters using tabu search , 2000 .

[39]  Armando Blanco,et al.  A real-coded genetic algorithm for training recurrent neural networks , 2001, Neural Networks.

[40]  S. Ho,et al.  A common Tabu search algorithm for the global optimization of engineering problems , 2001 .

[41]  F. Franze,et al.  A tabu‐search‐based algorithm for continuous multiminima problems , 2001 .

[42]  Jasmina Arifovic,et al.  Using genetic algorithms to select architecture of a feedforward artificial neural network , 2001 .

[43]  J. J. Hopfield,et al.  “Neural” computation of decisions in optimization problems , 1985, Biological Cybernetics.