本論文針對演化計算的結構和設計方法，研究共生演化和群智慧為基礎的最佳化演算法及其應用。首先，引用基因調控網路建立基因調控為基礎之共生演化演算法，並配合驗證函數測試性能與獲得模糊控制倒單擺系統和類神經控制天線臂系統之最佳化參數。其次，針對共生演化所獲得之平均適應值，利用群智慧的方式和基因階級來設計粒子群為基礎之共生演化演算法並針對實驗結果進行定量分析與定性分析。接著，本論文提出以生態學的論理式成長模型和生物學的共生關係之生態-生物行為為基礎之粒子群最佳化演算法，並應用在串級式非線性系統模糊滑動模式控制上。在模糊滑動模式控制方面，其模糊系統的設計方式，係運用李亞普諾夫定理所提供的能量衰減原理和受控對象的數學模型，針對模糊滑動模式控制器的控制輸入做即時的調整。在基於演化計算之模糊滑動模式控制器方面，乃採用所提出演化演算法將模糊滑動模式控制器之輸入和輸出尺度因子予以最佳化。最後，根據李亞普諾夫定理分析閉迴路系統的穩定性和推導模糊系統的規則和封閉數學式。本論文所提出的共生演化為基礎和群智慧為基礎的演化計算，經驗證函數模擬測試並與傳統演化計算在基因演算法、共生演化及粒子群最佳化等方面相比較，均有更佳的性能。

In this dissertation, studies and applications on the symbiotic evolution (SE)-based and the swarm intelligence (SI)-based optimization algorithms of structures and design methodologies for evolutionary computation (EC) are presented. Firstly, the genetic regulatory network-based symbiotic evolutionary (GRNSE) algorithm is proposed by using a genetic regulatory network (GRN). The performance of the proposed optimization algorithm is verified by using benchmark problem. Besides, the parameters in the fuzzy control scheme of the inverted pendulum system and the neural network control scheme of the antenna arm system are determined by the optimization algorithm. Secondly, the design schemes of the particle swarm-based symbiotic evolutionary (PSSE) algorithm are addressed by using the swarm intelligence and gene hierarchy according to the average fitness value of symbiotic evolution. The quantitative analysis and the qualitative analysis of experimental results are performed. Finally, we adopt the logical growth model of ecology and symbiotic relationship of biology then present the ecological-biological behavior-based particle swarm optimization (EBB-PSO) algorithm. The proposed algorithm is verified by the benchmark problem and it is applied to optimize fuzzy sliding-mode control (FSMC) for a cascade nonlinear system. In the FSMC, the control input of sliding-mode for the FSMC is tuned by the fuzzy system which is proved by the Lyapunov stability theory and by the mathematic model of sliding surface. In the EC-based FSMC, the EBB-PSO algorithm is utilized to find the global optimization scaling factors of the input and output variables for the FSMC. Finally, the global asymptotical stability of the EC-based FSMC, the closed-from of fuzzy system, and the fuzzy rule of fuzzy system are confirmed by the Lyapunov stability theory. Verifications of benchmarks demonstrate that three proposed evolutionary computation algorithms are effective and can provide much better performance in comparison with conventional evolutionary computations on the genetic algorithm (GA), symbiotic evolution (SE), and particle swarm optimization (PSO).

References

[1] Ackley, D. H., A Connectionist Machine for Genetic Hillclimbing, Kluwer Academic, 1987.
[2] Ali, M. M., C. Khompatraporn, and Z. B. Zabinsky, 「A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems,」 Journal of Global Optimization, Vol. 31, No. 4, 2005, pp. 635-672.
[3] Alleyne, A., 「Physical Insights on Passivity-Based TORA Control Designs,」 IEEE Transaction on Control Systems Technology, Vol. 6, No. 3, 1998, pp. 436-439.
[4] Ando, S. and H. Iba, 「Inference of Gene Regulatory Model by Genetic Algorithms,」 in Proceedings of International conference Evolution Computing, Vol. 1, 2001, pp. 712-719.
[5] Ando, S., E. Sakamoto, and H. Iba, 「Evolution Modeling and Inference of Gene Network,」 Information Sciences, Vol. 145, 2002, pp. 237-259.
[6] Andre, J., P. Siarry, and T. Dognon, 「An Improvement of the Standard Genetic Algorithm Fighting Premature Convergence in Continuous Optimization,」 Advance in Engineering Software, Vol. 32, No. 1, 2000, pp. 49-60.
[7] Back, T., Evolutionary Algorithms in Theory and Practice, Oxford, New York, 1996.
[8] Bernstein, D. S., Ed., 「Special Issue: A Nonlinear Benchmark Problem,」 International Journal of Robust Nonlinear Control, Vol. 8, No. 3-5, 1998, pp. 305-461.
[9] Beveridge, J. R., K. Balasubramaniam, and D. Whitley, 「Matching Horizon Features using a Messy Genetic Algorithm,」 Computer Methods in Applied Mechanics and Engineering, Vol. 186, No. 2-4, 2000, pp. 499-516.
[10] Bull, L., 「Evolutionary Computing in Multi-Agent Environments: Partners,」 in Proceedings of the 7th International on Conference Genetic Algorithms, 1997, pp. 370-377.
[11] Cai, X., Z. Cui, J. Zeng and Y. Tan, 「Particle Swarm Optimization with Self-Adjusting Cognitive Selection Strategy,」 International Journal of Innovative Computing, Information and Control, Vol. 4, No. 4, 2008, pp. 943-952.
[12] Cai, X., Z. Cui, J. Zeng, and Y. Tan, 「Performance-Dependent Adaptive Particle Swarm Optimization,」 International Journal of Innovative Computing, Information and Control, Vol. 3, No. 6(B), 2007, pp. 1697-1706.
[13] Cao, X. B., W. J. Luo, and X. F. Wang, 「A Co-Evolution Pattern Based on Ecological Population Competition Model,」 Journal of Software, Vol. 12, No. 4, 2001, pp. 556-562.
[14] Chang, P. C., S. H. Chen, and K. L. Lin, 「Two-Phase Sub Population Genetic Algorithm for Parallel Machine-Scheduling Problem,」 Expert Systems with Applications, Vol. 29, No. 3, 2005, pp. 705-712.
[15] Chen, C. H., C. J. Lin and C. T. Lin, 「Using an Efficient Immune Symbiotic Evolution Learning for Compensatory Neuro-Fuzzy Controller,」 IEEE Transaction on Fuzzy Systems, Vol.17, No.3, 2009, pp. 668-682.
[16] Chen, J. L. and W. D. Chang, 「Feedback Linearization Control of a Two-Link Robot using a Multi-Crossover Genetic Algorithm,」 Expert Systems with Applications, Vol. 36, No. 2, 2009, pp. 4154-4159.
[17] Chen, L. S., Mathematical Ecology Model and Research Method, Scientific Publishers, 1988.
[18] Cohoon, J. P., S. U. Hegde, W. N. Martin, and D. S. Richards, 「Distributed Genetic Algorithms for the Floorplan Design Problem,」 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 10, No. 4, 1991, pp. 483-492.
[19] Cui, Z. H., J. C. Zeng, and X. J. Cai, 「A New Stochastic Particle Swarm Optimizer,」 in Proceedings of the IEEE Congress on Evolutionary Computation, 2004, pp. 316-319.
[20] Cui, Z., G. Sun and J. Zeng, 「A Fast Particle Swarm Optimization,」 International Journal of Innovative Computing, Information and Control, Vol.2, No.1, 2006, pp. 1365-1380.
[21] Cui, Z., X. Cai, and J. Zeng, 「Chaotic Performance-Dependent Particle Swarm Optimization,」 International Journal of Innovative Computing, Information and Control, Vol. 5, No. 4, 2009, pp. 951-960.
[22] Diong, B. M., 「A Sliding-Mode Control Approach to the Benchmark Problem for Nonlinear Control Design,」 in Proceedings of IECON』97, 1997, pp. 68-72.
[23] Droste, S., T. Jansen, and I. Wegener, 「On the Analysis of the (1+1) Evolutionary Algorithm,」 Theoretical Computer Science, Vol. 276, No. 1, 2002, pp. 51-81.
[24] Elliot, R. and R. Vasta, 「Effects Associated with Vicarious Reinforcement, Symbolization, Age, and Generalization,」 Journal of Experimental Child Psychology, Vol. 10, 1970, pp. 8-15.
[25] Fogel, L. J., A. J. Owens, and M. J. Walsh, Artificial Intelligence through Simulated Evolution, Wiley, New York, 1966.
[26] Gao, W. and J. C. Hung, 「Variable Structure Control of Nonlinear Systems: A New Approach,」 IEEE Transaction on Industrial Electronics, Vol. 40, No. 1, 1993, pp. 45-55.
[27] Goldberg, D., K. Deb, and B. Korb, 「Messy Genetic Algorithms: Motivation, Analysis, and First Results,」 Complex Systems, Vol. 3, No. 5, 1989, pp. 493-530.
[28] Goldstein, H., Classical Mechanics, A. W., 1980.
[29] Golgberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning, Reading, MA: Addison-Wesley, Boston, 1989.
[30] Goulermas, J. Y. and P. Liatsis, 「A Collective-Based Adaptive Symbiotic Model for Surface Reconstruction in Area-Based Stereo,」 IEEE Transactions on Evolutionary Computation, Vol.7, No.5, 2003, pp. 482-502.
[31] Guo, Y., X. Cao, H. Yin and Z. Tang, 「Coevolutionary Optimization Algorithm with Dynamic Sub-Population Size,」 International Journal of Innovative Computing, Information and Control, Vol.3, No.2, 2007, pp. 435-448.
[32] Hara, Y. and Y. Ebino, 「Advanced Ubiquitous System Technologies for Symbiotic Evolution,」 Journal of advanced technology, Vol. 2, No. 2, 2005, pp. 164-169.
[33] Hinchey, M. G., R. Sterritt and C. Rouff, 「Swarms and Swarm Intelligence,」 IEEE Computer Society, Vol. 40, No. 4, 2007, pp. 111-113.
[34] Hock, W. and K. Schittkowski, Test Examples for Nonlinear Programming Codes. Springer-Verlag, Berlin, Heidelberg, 1981.
[35] Holland, J. H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press, 1975.
[36] Hrstka, O. and A. Ku˘cerová, 「Improvement of Real Coded Genetic Algorithm Based on Differential Operators Preventing Premature Convergence,」 Advance in Engineering Software, Vol. 35, No. 3-4, 2004, pp. 237-246.
[37] Hsu, F. C. and J. S. Chen, 「A Study on Multi Criteria Decision Making Model: Interactive Genetic Algorithms Approach,」 Tamsui Oxford Journal of Management Sciences, Vol. 17, No. 15, 1999, pp. 145-163.
[38] Hu, J. J. and J. P. Su, Fuzzy Lyapunov Variable Structure Control of a Class of Cascade-Connected Nonlinear Systems and Its Application to a Twin-Rotor Multi-Input Multi-Output System. Master Thesis, Department of Electrical Engineering, National Yunlin University of Science and Technology, Taiwan, 2005.
[39] Huang, M. J., H. S. Huang, and M. Y. Chen, 「Constructing a Personalized E-Learning System Based on Genetic Algorithm and Case-Based Reasoning Approach,」 Expert Systems with Applications, Vol. 33, No.3, 2007, pp. 551-564.
[40] Hussain, T. S., An Introduction to Evolutionary Computation, Department of Computing and Information Science, Queen』s University, Kingston, Ont. K7L 3N6.
[41] Iba, H. and A. Mimura, 「Inference of a Gene Regulatory Network by Means of Interactive Evolutionary Computing,」 Information Sciences, Vol. 145, No. 3-4, 2002, pp. 225-236.
[42] Igel, C. and M. Toussaint, 「A No-Free-Lunch Theorem for Non-Uniform Distributions of Target Functions,」 Journal of Mathematical Modeling and Algorithms, Vol. 3, No. 4, 2005, pp. 313-322.
[43] Jang, J. S. R., Neuro-Fuzzy and Soft Computing, Prentice-Hall, 1997.
[44] Jankovic, M., D. Fontaine, and P. V. Kokotovic, 「TORA Example: Cascade- and Passive-Based Control Designs,」 IEEE Transaction on Control Systems Technology, Vol. 4, No. 3, 1996, pp. 292-297.
[45] Jiang, W., Y. Xu, and Y. Xu, 「A Novel Application of Neural Network Optimized Design Based on Immune Modulated Symbiotic Evolution,」 International Journal of Information Technology, Vol. 12, No. 3, 2006, pp. 33-42.
[46] Juang, C. F., J. Y. Lin, and C. T. Lin, 「Genetic Reinforcement Learning through Symbiotic Evolution for Fuzzy Controller Design,」 IEEE Transactions on Systems, Man, and Cybernetics, Part B, Vol. 30, No. 2, 2000, pp. 290-302.
[47] Kang, Q., L. Wang, and Q. Wu, 「A Novel Ecological Particle Swarm Optimization Algorithm and Its Population Dynamics Analysis,」 Applied Mathematics and Computation, Vol. 205, No. 1, 2008, pp. 61-72.
[48] Kang, Q., L. Wang, H. Xiao and Q. Wu, 「Evaluation Mode Research on Particle Swarm Optimization Algorithm,」 in Proceedings of IEEE International Conference on Networking, Sensing and Control, London, UK, 2007, pp.15-17.
[49] Kaya, I., 「A Genetic Algorithm Approach to Determine the Sample Size for Control Charts with Variables and Attributes,」 Expert Systems with Applications, Vol. 36, No. 5, 2009, pp. 8719-8734.
[50] Kennedy, J. and R. C. Eberhart, Swarm Intelligence. Morgan Kaufmann, 2001.
[51] Kennedy, J. and R. Eberhart, 「Particle Swarm Optimization,」 in Proceedings of IEEE International Conference on Neural Networks, 1995, pp.1942-1948.
[52] Kennedy, J., 「The Particle Swarm: Social Adaptation of Knowledge,」 in Proceedings of IEEE International Conference on Evolutionary Computation, 1997, pp. 303-308.
[53] Kim, J. Y., Y. Kim and Y. K. Kim, 「An Endosymbiotic Evolutionary Algorithm for Optimization,」 Applied Intelligence, Vol.15, No.2, 2001, pp. 117-130.
[54] Kim, Y. K., J. Y. Kim, and Y. Kim, 「An Endosymbiotic Evolutionary Algorithm for the Integration of Balancing and Sequencing in Mixed-Model U-lines,」 European Journal of Operational Research, Vol. 168, No. 3, 2006, pp. 838-852.
[55] Kim, Y. K., K. Park, and J. Ko, 「A Symbiotic Evolutionary Algorithm for the Integration of Process Planning and Job Shop Scheduling,」 Computers and Operations Research, Vol. 30, No. 8, 2003, pp. 1151-1171.
[56] Knjazew, D. and D. E. Goldberg, Solving Permutation Problems with the Ordering Messy Genetic Algorithm, Advances in Evolutionary Computing: Theory and Applications, Springer-Verlag, New York, 2003.
[57] Koumousis, V. K. and C. P. Katsaras, 「A Sawtooth Genetic Algorithm Combining the Effects of Variable Population Size and Reinitialization to Enhance Performance,」 IEEE Transactions on Evolutionary Computation, Vol. 10, No. 1, 2006, pp. 19-28.
[58] Koza, J. R., 「Hierarchical Genetic Algorithms Operating on Populations of Computer Programs,」 in Proceedings of International Joint conference on Artificial Intelligence, Vol. 1, No. 20-25, 1989, pp. 768-774.
[59] Koza, J. R., Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge: MIT Press, 1992.
[60] Kumamoto, A., A. Utani, and H. Yamamoto, 「Advanced Particle Swam Optimization for Computing Plural Acceptable Solutions,」 International Journal of Innovative Computing, Information and Control, Vol. 5, No. 11(B), 2009, pp. 4383-4392.
[61] Kuo, H. C. and H. K. Chang, 「A New Symbiotic Evolution-Based Fuzzy-Neural Approach to Fault Diagnosis of Marine Propulsion Systems,」 Engineering Applications of Artificial Intelligence, Vol. 17, No. 8, 2004, pp. 919-930.
[62] Kuo, H. C., H. K. Chang, and Y. Z. Wang, 「Symbiotic Evolution-Based Design of Fuzzy-Neural Diagnostic System for Common Acute Abdominal Pain,」 Expert Systems with Applications, Vol. 27, No. 3, 2004, pp. 391-401.
[63] Li, J. M., D. L. Wan, Z. X. Chi, and X. P. Hu, 「An Efficient Fine-Grained Parallel Particle Swarm Optimization Method Based on GPU-Acceleration,」 International Journal of Innovative Computing, Information and Control, Vol. 3, No. 6(B), 2007, pp. 1707-1714.
[64] Li, Y., S. Zhang, and X. Zeng, 「Research of Multi-Population Agent Genetic Algorithm for Feature Selection,」 Expert Systems with Applications, Vol. 36, No. 9, 2009, pp. 11570-11581.
[65] Liang, W. Y. and C. C. Huang, 「The Generic Genetic Algorithm Incorporates with Rough Set Theory - An Application of the Web Services Composition,」 Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 5549-5556.
[66] Lin, C. J. and C. F. Wu, 「An Efficient Symbiotic Particle Swarm Optimization for Recurrent Functional Neural Fuzzy Network Design,」 International Journal of Fuzzy Systems, Vol. 11, No. 4, 2009, pp. 262-271.
[67] Lin, C. J. and Y. J. Xu, 「A Self-Adaptive Neural Fuzzy Network with Group-Based Symbiotic Evolution and Its Prediction Applications,」 Fuzzy Sets and Systems, Vol.157, No.8, 2006, pp. 1036-1056.
[68] Lin, C. J. and Y. J. Xu, 「A Self-Constructing Neural Fuzzy Network with Dynamic-Form Symbiotic Evolution,」 Auto Soft Journal-Intelligent Automation and Soft Computing, Vol.13, No.2, 2007, pp. 123-137.
[69] Lin, C. J., 「An Efficient Immune-Based Symbiotic Particle Swarm Optimization Learning Algorithm for TSK-Type Neuro-Fuzzy Networks Design,」 Fuzzy Sets and Systems, Vol. 159, No. 21, 2008, pp. 2890-2909.
[70] Lin, C. J., C. H. Chen, and C. T. Lin, 「Efficient Self-Evolving Evolutionary Learning for Neuro-Fuzzy Inference Systems,」 IEEE Transactions on Fuzzy Systems, Vol. 16, No. 6, pp. 2008, pp. 1476-1490.
[71] Liu, F. and G. Zeng 「Study of Genetic Algorithm with Reinforcement Learning to Solve the TSP,」 Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 6995-7001.
[72] Liu, H., B. Li, Y. Ji, and Y. Tang, 「Survival Density Particle Swarm Optimization for Neural Network Training,」 Lecture Notes in Computer Science, Springer, Vol. 3173, 2004, pp. 332-337.
[73] Liu, J. and J. Lampinen, 「A Fuzzy Adaptive Differential Evolution Algorithm. Soft Computing-A Fusion of Foundations,」 Methodologies and Applications, Vol. 9, No. 6, 2005, pp. 448-462.
[74] Mahdavi, I., M. M. Paydar, M. Solimanpur, and A. Heidarzade, 「Genetic Algorithm Approach for Solving a Cell Formation Problem in Cellular Manufacturing,」 Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 6598-6604.
[75] Man, K. F., K. S. Tang, and S. Kwong, 「Genetic Algorithms: Concepts and Applications,」 IEEE Transaction on Indusial Electronic, Vol. 43, No. 5, 1996, pp. 519-534.
[76] Margaliot, M. and G. Langholz, 「Fuzzy Control of a Benchmark Problem: a Computing with Words Approach,」 IEEE Transaction on Fuzzy Systems, Vol. 12, No. 2, 2004, pp. 230-235.
[77] Margulis, L. and D. Sagan, What Is Sex? Simon & Schuster; 1st edition, 1998.
[78] Margulis, L., Symbiosis as a Source of Evolutionary Innovation: Speciation and Morphogenesis, The MIT Press, 1991.
[79] Margulis, L., Symbiosis in Cell Evolution, WH Freeman, San Francisco, 1980.
[80] Maury, M., J. Gouvea and F. R. A. Aluizio, 「Population Dynamics Model for Gene Frequency Prediction in Evolutionary Algorithm,」 in Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2008), 2008, pp.1603-1610.
[81] McDermott, A., 「Chromosome Hierarchy: An Introduction to the Biology of the Chromosome,」 Journal of Medical Genetics, Vol. 13, No. 5, 1976, pp. 414.
[82] Michalewicz, Z. and M. Schoenauer, 「Evolutionary Algorithms for Constrained Parameter Optimization Problems,」 Evolutionary Computation, Vol. 4, No. 1, 1996, pp. 1-32.
[83] Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, Berlin, 1996.
[84] Min, S. H., J. Lee, and I. Han, 「Hybrid Genetic Algorithms and Support Vector Machines for Bankruptcy Prediction.」 Expert Systems with Applications, Vol. 31, No.3, 2006, pp. 652-660.
[85] Monson, C. K. and K. D. Seppi, 「The Kalman Swarm: a New Approach to Particle Motion in Swarm Optimization,」 in Proceedings of the Genetic and Evolutionary Computation Conference, 2004, pp. 140-150.
[86] Moriarty, D. E. and R. Miikkulainen, 「Forming Neural Networks through Efficient and Adaptive Coevolution,」 Evolutionary Computation, Vol.5, No.4, 1997, pp. 373-399.
[87] Moriarty, D. E., R. Miikkulainen, and P. Kaelbling, 「Efficient Reinforcement Learning through Symbiotic Evolution,」 Machine Learning, Vol. 22, No.1-3, 1996, pp.11-32.
[88] Moriarty, D. E., Symbiotic Evolution of Neural Networks in Sequential Decision Tasks, Ph. D. Dissertation, the University of Texas at Austin, 1997.
[89] Morrison, R. W. and K. A. De Jong, 「Triggered Hypermutation Revisited,」 in Proceedings of the 2000 Congress on Evolutionary Computation, Vol. 2, No. 16-19, 2000, pp. 1025-1032.
[90] Oh, S. K., S. H. Jung, and W. Pedrycz, 「Design of Optimized Fuzzy Cascade Controllers by Means of Hierarchical Fair Competition-Based Genetic Algorithms,」 Expert Systems with Applications, Vol. 36, No. 9, 2009, pp. 11641-11651.
[91] Pan, J. C. H. and H. C. Huang, 「A Hybrid Genetic Algorithm for No-Wait Job Shop Scheduling Problems,」 Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 5800-5806.
[92] Pan, S. T. and C. C. Lai, 「Identication of Chaotic Systems by Neural Network with Hybrid Learning Algorithm,」 Chaos, Solitons and Fractals. Vol. 37, No. 1, 2008, pp. 233-244.
[93] Paredis, J., 「The Symbiotic Evolution of Solutions and Their Representations,」 in Proceedings of the 6th International Conference on Genetic Algorithms, 1995, pp.359-365.
[94] Peck, C. C. and A. P. Dhawan, 「Genetic Algorithms as Global Random Search Methods: An Alternative Perspective,」 Evolutionary Computation, Vol. 3, No. 1, 1995, pp. 39-80.
[95] Potter, M. A., The Design and Analysis of a Computational Model of Cooperative Coevolution, Ph.D. dissertation, George Mason University, USA, 1997.
[96] Price, K., R. M. Storn, and J. A. Lampinen, Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series), Springer, New York, 2005.
[97] Quagliarella, D., J. Periaux, C. Poloni, and G. Winter, Genetic Algorithms and Evolution Strategy in Engineering and Computer Science: Recent Advances and Industrial Applications. John Wiley & Sons Ltd, 1998.
[98] Reeves, C. R., 「Using Genetic Algorithms with Small Populations,」 in Proceedings of the 5th International Conference on Genetic Algorithms, 1993, pp. 92-99.
[99] Riget, J. and J. S. Vesterstroem, Diversity Guided Particle Swarm Optimizer-The ARPSO, Aarhus: University of Aarhus. EVALife, 2002.
[100] Rosin, C. D. and R. K. Belew, 「New Methods for Competitive Coevolution,」 Evolutionary Computation. Vol. 5, No. 1, 1997, pp. 1-29.
[101] Shahookar, K. and P. Mazumder, 「A Genetic Approach to Standard Cell Placement using Meta-Genetic Parameter Optimization,」 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 9, No. 5, 1990, pp. 500-511.
[102] Shi, Y. and R. C. Eberhart, 「Empirical Study of Particle Swarm Optimization,」 in Proceedings of the Congress on Evolutionary Computation, 1999, pp. 1945-1962.
[103] Shi, Y. and R. C. Eberhart, 「Fuzzy Adaptive Particle Swarm Optimization,」 in Proceedings of the Congress on Evolutionary Computation, 2001, pp. 101-106.
[104] Shi, Y. and R. C. Eberhat, 「A Modified Particle Swarm Optimizer,」 in Proceedings of the IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, 1998, pp. 63-73,.
[105] Shi, Y. and R. C. Eberhat, 「Parameter Selection in Particle Swarm Optimization,」 in Proceedings of the 7th Annual Conference on Evolutionary Programming, 1998, pp. 591-600.
[106] Slotine, J. J. E. and W. Li, Applied Nonlinear Control, Prentice Hall, 1991.
[107] Song, W., C. H. Li, and S. C. Park, 「Genetic Algorithm for Text Clustering using Ontology and Evaluating the Validity of Various Semantic Similarity Measures,」 Expert Systems with Applications, Vol. 36, No. 5, 2009, pp. 9095-9104.
[108] Su, J. P., 「Robust Control of a Class of Nonlinear Cascade Systems: A Novel Sliding-Mode Approach,」 IEE Proceedings Control Theory and Applications, Vol. 149, No. 2, 2002, pp. 131-136.
[109] Su, M. C. and C. C. Hung, Ed., 「Special Issue: Swarm Intelligence and Its Applications in Fuzzy Systems,」 International Journal of Fuzzy Systems, Vol. 10, No. 3, 2008, pp. 137-217.
[110] Suganthan, P. N., 「Particle Swarm Optimizer with Neighborhood Operator,」 in Proceedings of the Congress on Evolutionary Computation, 1999, pp. 1958-1962.
[111] Suganthan, P. N., N. Hansen, J. J. Liang, K. Deb, Y. P. Chen, A. Auger, and S. Tiwari, 「Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization,」 Nanyang Tech. Univ., Singapore and KanGAL, Kanpur Genetic Algorithms Lab., IIT, Kanpur, India, Tech. Rep., 2005.
[112] Sun, J., 「Particle Swarm Optimization with Particles Having Quantum Behavior,」 the IEEE Congress on Evolutionary Computation, 2004, pp.325-331.
[113] Syswerda, G., 「Uniform Crossover in Genetic Algorithms,」 in Proceedings of the 3rd International Conference on Genetic Algorithms, 1989, pp. 2-9.
[114] Tadmor, G., 「Dissipative Design, Lossless Dynamics, and the Nonlinear TORA Benchmark Example,」 IEEE Transaction on Control Systems Technology, Vol. 9, No. 2, 2001, pp. .
[115] Tang, A. M., C. Quek, and G. S. Ng, 「GA-TSKfnn: Parameters Tuning of Fuzzy Neural Network using Genetic Algorithms,」 Expert Systems with Applications, Vol. 29, No. 4, 2005, pp. 769-781.
[116] Thorndike, E. L., Animal Intelligence: Experimental Studies, Macmillan, New York, 2009.
[117] Trelea, I. C., 「The Particle Swarm Optimization Algorithm: Convergence Analysis and Parameter Selection,」 Information Processing Letters, Vol. 85, No. 6, 2003, pp. 317-325.
[118] Tsai, J. T., W. H. Ho, and J. H. Chou, 「Design of Two-Dimensional IIR Digital Structure-Specified Filters by using an Improved Genetic Algorithm,」 Expert Systems with Applications, Vol. 36, No. 3, 2009, pp. 6928-6934.
[119] Tsai, J. T., W. H. Ho, T. K. Liu, and J. H. Chou, 「Improved Immune Algorithm for Global Numerical Optimization and Job-Shop Scheduling Problems,」 Applied Mathematics and Computation, Vol. 194, No. 2, 2007, pp. 406-424.
[120] Tsutsui, S., M. Pelikan and G. Ashish, 「Performance of Aggregation Pheromone System on Unimodal and Multimodal Problems,」 in Proceedings of the 2005 IEEE Congress on Evolutionary Computation, Vol. 1, 2005, pp. 880-887.
[121] Vesterstroem, J. and R. Thomsen, 「A Comparative Study of Differential Evolution, Particle Swarm Optimization, and Evolutionary Algorithms on Numerical Benchmark Problems,」 in Proceedings of the Congress Evolutionary Computation, Vol. 2, No. 19-23, 2004, pp. 1980-1987.
[122] Wai, R. J., M. A. Kuo, and J. D. Lee, 「Design of Cascade Adaptive Fuzzy Sliding-Mode Control for Nonlinear Two-Axis Inverted-Pendulum Servomechanism,」 IEEE Transaction on Fuzzy Systems, Vol. 16, No. 5, 2008, pp. 1232-1244.
[123] Wang, H. S., Z. H. Che and C. Wu, 「Using Analytic Hierarchy Process and Particle Swarm Optimization Algorithm for Evaluating Product Plans,」 Expert Systems with Applications, Vol. 37, No. 2, 2010, pp. 1023-1034.
[124] Wu, S. J. and P. T. Chow, 「Genetic Algorithms for Nonlinear Mixed Discrete-Integer Meta-Genetic Parameter Optimization,」 Engineering Optimization, Vol. 24, No. 2, 1995, pp. 137-159.
[125] Xiaofeng, Q. and F. Palmieri, 「Theoretical Analysis of Evolutionary Algorithms with an Infinite Population Size in Continuous Space. Part I: Basic Properties of Selection and Mutation,」 IEEE Transactions on Neural Networks, Vol. 5, No. 1, 1994, pp. 102-119.
[126] Yamamura, M., H. Satoh, and S. Kobayashi, 「An Analysis of Crossover』s Effect in Genetic Algorithms. Evolutionary Computation,」 in Proceedings of the IEEE World Congress on Computational Intelligence, Vol. 2, No. 27-29, 1994, pp. 613-618.
[127] Yang, H. H. and C. L. Lin, 「On Genetic Algorithms for Shoe Making Nesting - A Taiwan Case,」 Expert Systems with Applications, Vol. 36, No. 2, 2009, pp. 1134-1141.
[128] Yang, S., Statistics-Based Adaptive Non-Uniform Mutation for Genetic Algorithms, Lecture Notes in Computer Science, Genetic and Evolutionary Computation-GECCO 2003. Springer Berlin: Heidelberg, 2003.
[129] Yasuda, K. and N. Iwasaki, 「Adaptive Particle Swarm Optimization via Velocity Feedback,」 International Journal of Innovative Computing, Information and Control, Vol. 1, No. 3, 2005, pp. 423-432.
[130] Yeh, J. Y. and J. C. Fu, 「A Hierarchical Genetic Algorithm for Segmentation of Multi-Spectral Human-Brain MRI,」 Expert Systems with Applications, Vol. 34, No. 2, 2008, pp. 1285-1295.
[131] Zhao, J., B. Knight, E. Nissan, and A. Soper, 「FuelGen: A Genetic Algorithm-Based System for Fuel Loading Pattern Design in Nuclear Power Reactors,」 Expert Systems with Applications, Vol. 14. No. 4, 1998, pp. 461-470.
[132] Zheng, Y. L., L. H. Ma, L. Y. Zhang, and J. X. Qian, 「On the Convergence Analysis and Parameter Selection in Particle Swarm Optimization, in Proceedings of the Second International Conference on Machine Learning and Cybernetics, Xi』an, China, 2003, pp. 1802-1807.