[1] Aarts E., Korst J. (1989), Simulated Annealing and Boltzmann Machines: A Stochastic Approach to
Combinatorial Optimization and Neural Computing; Wiley, New York.
[2] Aras N., Altınel I.K., Oommen J. (2003), A Kohonen-Like Decomposition Method For The Euclidean
Traveling Salesman Problem Knies-Decompose; IEEE Transactions on Neural Network 14(4).
[3] Chen H., Flann S.N., Watson W.D. (1998), Parallel Genetic Simulated Annealing: A Massively
Parallel SIMD Algorithm; IEEE Transactions on Parallel and Distributed Systems 9(2); 126-136.
[4] Cheng C.-H., Lee W.-K., Wong K.-F. (2002), A Genetic Algorithm-Based Clustering Approach for
Database Partitioning; IEEE Transactions on Systems, Man, and Cybernetics—PART C: Applications
and Reviews 32(3).
[5] Cho H.J., Young Oh S., Choi D.-H. (1998), Population-oriented simulated annealing technique based
on local Temperature concept; Electronics Letters 34(3); 312-313.
[6] Creput J.C., Koukam A. (2008), A memetic neural network for the Euclidean traveling salesman
problem; Neurocomputing.
[7] Dueck G., Scheuer T. (1990), Threshold accepting: A general purpose optimization algorithm
appearing superior to simulated annealing; J. Computer. Phys. 90; 161–175.
[8] Garey M.R., Johnson D.S. (1979), Computers and Intractability: A Guide to the Theory of NPCompleteness;
Freeman, New York.
[9] He Y. (2002), Chaotic Simulated Annealing With Decaying Chaotic Noise; IEEE Transactions on
Neural Networks 13(6); 1526-1531.
[10] Hung M.-H., Shu L.-S., Ho S.-J., Hwang S.-F., Ho S.-Y. (2008); A Novel Intelligent Multiobjective
Simulated Annealing Algorithm for Designing Robust PID Controllers; Proceeding of IEEE
Transactions on Systems, Man, and Cybernetics—PART A: Systems and Humans 38(2); 319-330.
[11] Ingber L., Rosen B. (1992), Genetic Algorithms and Very Fast Simulated Reannealing: A Comparison;
Mathematical Computer Modeling 16(11); 87-100.
[12] Jang J., Sun C., Mizutani E. (1997), Neuro-Fuzzy and Soft Computing; Proc. of the Prentice Hall.
[13] Jin H.-D., Leung K.-S., Wong M.-L., Xu Z.-B. (2003), An Efficient Self-Organizing Map Designed by
Genetic Algorithms for the Traveling Salesman Problem; IEEE Transactions on Systems, Man, and
Cybernetics—PART B: Cybernetics 33(6); 877-888.
[14] Kirkpatrick S., Gelatt C.D., Vecchi M.P. (1983), Optimization by simulated annealing; Science 220;
671–680.
[15] Kravitz S.A., Rutenbar R.A. (1987), Placement by simulated annealing on a multiprocessor; IEEE
Trans. Computer-Aided Design Integr. Circuits Syst. 6(4); 534–549.
[16] Leung K.-S., Jin H.-D., Xu Z.-B. (2004), An expanding Self-Organizing neural network for the
traveling salesman problem; Neurocomputing 62; 267-292.
[17] Lin F.-T., Kao C.-Y., Hsu C.-C. (1993), Applying the Genetic Approach to Simulated Annealing in
Solving Some NP-Hard Problems; IEEE Transactions on Systems, Man, and Cybernetics, 23(6).
[18] Pao D.C.W., Lam S.P., Fong A.S. (1999), Parallel implementation of simulated annealing using
transaction processing; IEE Proc-Comput. Digit. Tech.. 146(2); 107-113.
[19] Pepper W.J., Golden L.B., Wasil A.E. (2002), Solving the Traveling Salesman Problem With
Annealing-Based Heuristics: A Computational Study; IEEE Transactions on Systems, Man, and
Cybernetics—PART A: Systems and Humans 32(1).
[20] Saadatmand-Tarzjan M., Khademi M., Akbarzadeh M.R.., Abrishami Moghaddam H. (2007), A Novel
Constructive-Optimizer Neural Network for the Traveling Salesman Problem; IEEE Transactions on
Systems, Man, and Cybernetics—PART B: Cybernetics 37(4).
[21] Shakouri G.H., Shojaee K., Behnam T.M. (2009), The Wise Experiencing Traveling Salesman
(WETS): Introduction to a simple evolutionary solution for the problem; Proc. in CEC 2009 IEEE
Congress on Evolutionary Computation; 18-21 May, Trondheim, Norway; 771-776.
[22] Smith K.I., Everson M.R., Fieldsend E.J, Murphy C., Misra R. (2008), Dominance-Based
Multiobjective Simulated Annealing; IEEE Transactions on Evolutionary Computation 12(3); 323-
341.
[23] Soh A. (1995), Parallel N-ary Speculative Computation of Simulated Annealing; IEEE Transactions
on Parallel and Distributed Systems 6(10); 997-1005.
[24] Thompson R.D., Bilbro L.G. (2005), Sample-Sort Simulated Annealing; IEEE Transactions on
Systems, Man, and Cybernetics—PART B: Cybernetics 35(3); 625-632.
[25] Tsang H.H., Wiese K.C. (2007), The Significance of Thermodynamic Models in the Accuracy
Improvement of RNA Secondary Structure Prediction Using Permutation-based Simulated Annealing;
Proceeding of IEEE Congress on Evolutionary Computation.
[26] Wang L., Li S., Tian F., Fu X. (2004), A Noisy Chaotic Neural Network for Solving Combinatorial
Optimization Problems: Stochastic Chaotic Simulated Annealing; Transactions on Systems, Man, and
Cybernetics—PART B: Cybernetics 34(5); 2119-2125.
[27] Wong K.L., Constantinides A.G. (1998), Speculative parallel simulated annealing with acceptance
prediction; Electronics Letters 34(3); 312-313.
[28] Wu S., Chow W.S.T. (2007), Self-Organizing and Self-Evolving Neurons: A New Neural Network for
Optimization; IEEE Transactions on Neural Network 18(2); 385-396.
[29] Yip C.P., Pao Y.-H. (1995), Combinatorial Optimization with Use of Guided Evolutionary Simulated
Annealing; IEEE Transactions on Neural Networks 6(2); 290-295.
[30] Reinelt G. (1995), Tsplib95, http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95,
2010