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1

Li, Kangshun, Yong Liu, and Wenxiang Wang, eds. Exploration of Novel Intelligent Optimization Algorithms. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4109-2.

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2

Melin, Patricia, and Oscar Castillo, eds. New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53713-4.

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3

Tao, Fei, Lin Zhang, and Yuanjun Laili. Configurable Intelligent Optimization Algorithm. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08840-2.

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4

Romania) BICS 2008 (2008 Tîrgu-Mureș. BICS 2008: Proceedings of the 1st International Conference, Bio-inspired Computational Methods Used for Solving Difficult Problems--Development of Intelligent and Complex Systems : Tirgu Mures, Romania, 5-7 November 2008. Edited by Enachescu Calin, Iantovics Barna L, and Filip F. G. American Institute of Physics, 2009.

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5

Koziel, Slawomir. Computational Optimization, Methods and Algorithms. Springer Berlin Heidelberg, 2011.

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6

Shi, Yuhui. Emerging research on swarm intelligence and algorithm optimization. Information Science Reference, 2015.

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7

Alba, Enrique. Metaheuristics for Dynamic Optimization. Springer Berlin Heidelberg, 2013.

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8

Ünal, Muhammet. Optimization of PID Controllers Using Ant Colony and Genetic Algorithms. Springer Berlin Heidelberg, 2013.

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9

Rao, R. Venkata. Mechanical Design Optimization Using Advanced Optimization Techniques. Springer London, 2012.

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10

Vasiljević, Darko. Classical and Evolutionary Algorithms in the Optimization of Optical Systems. Springer US, 2002.

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11

Geem, Zong Woo. Harmony search algorithms for structural design optimization. Springer, 2009.

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12

J, Grefenstette John, American Association for Artificial Intelligence., Naval Research Laboratory (U.S.), and Bolt, Beranek, and Newman, inc., eds. Genetic algorithms and their applications: Proceedings of the second International Conference on Genetic Algorithms : July 28-31, 1987 at the Massachusetts Institute of Technology, Cambridge, MA. L. Erlbaum Associates, 1987.

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13

Zhang, Huaguang. Adaptive Dynamic Programming for Control: Algorithms and Stability. Springer London, 2013.

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14

Ferris, Michael C. Complementarity: Applications, Algorithms and Extensions. Springer US, 2001.

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15

Osman, Ibrahim H. Meta-Heuristics: Theory and Applications. Springer US, 1996.

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16

Solnon, Christine. Ant colony optimization and constraint programming. Ltd/John Wiley, 2010.

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17

Solnon, Christine. Ant colony optimization and constraint programming. Ltd/John Wiley, 2010.

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18

Intelligent Optimization: Principles, Algorithms and Applications. Springer, 2024.

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19

(Editor), William Annicchiarico, Jacques Periaux (Editor), Miguel Cerrolaza (Editor), and Gabriel Winter (Editor), eds. Evolutionary Algorithms And Intelligent Tools In Engineering Optimization. WIT Press (UK), 2005.

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20

Zhang, Lin, Fei Tao, and Yuanjun Laili. Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing. Springer, 2016.

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21

Zhang, Lin, Fei Tao, and Yuanjun Laili. Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing. Springer, 2014.

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22

Zhang, Lin, Fei Tao, and Yuanjun Laili. Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing. Springer, 2014.

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23

Learning And Intelligent Optimization. Springer, 2012.

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24

Balamurugan, S., Akash Kumar Bhoi, Sanjeevikumar Padmanaban, Neeraj Priyadarshi, and Jens Bo Holm-Nielson. Intelligent Renewable Energy Systems: Integrating Artificial Intelligence Techniques and Optimization Algorithms. Wiley & Sons, Incorporated, John, 2021.

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25

Intelligent Renewable Energy Systems: Integrating Artificial Intelligence Techniques and Optimization Algorithms. Wiley & Sons, Limited, John, 2022.

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26

Balamurugan, S., Akash Kumar Bhoi, Sanjeevikumar Padmanaban, Neeraj Priyadarshi, and Jens Bo Holm-Nielson. Intelligent Renewable Energy Systems: Integrating Artificial Intelligence Techniques and Optimization Algorithms. Wiley & Sons, Incorporated, John, 2021.

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27

Balamurugan, S., Akash Kumar Bhoi, Sanjeevikumar Padmanaban, Neeraj Priyadarshi, and Jens Bo Holm-Nielson. Intelligent Renewable Energy Systems: Integrating Artificial Intelligence Techniques and Optimization Algorithms. Wiley & Sons, Incorporated, John, 2021.

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28

Vanschoren, Joaquin, Meinolf Sellmann, and Paola Festa. Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, Revised Selected Papers. Springer, 2016.

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29

Dhaenens, Clarisse, Laetitia Jourdan, and Marie-Eléonore Marmion. Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers. Springer International Publishing AG, 2015.

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30

Dhaenens, Clarisse, Laetitia Jourdan, and Marie-Eléonore Marmion. Learning and Intelligent Optimization: 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers. Springer London, Limited, 2015.

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31

New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms. Springer, 2024.

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32

Hamadi, Youssef, and Marc Schoenauer. Learning and Intelligent Optimization: 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers. Springer, 2012.

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33

Evolutionary Optimization Algorithms. Taylor & Francis Group, 2021.

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34

Badar, Altaf Q. H. Evolutionary Optimization Algorithms. Taylor & Francis Group, 2021.

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35

Badar, Altaf Q. H. Evolutionary Optimization Algorithms. Taylor & Francis Group, 2021.

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36

Godwin Premi, Dr M. S., Dr D. Susitra, Dr Suja Cherukullapurath Mana, Ms R. Velvizhi, and Ms Manju C. Nair. QUANTUM COMPUTING. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2025. https://doi.org/10.47716/978-93-92090-62-2.

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Abstract:
Quantum Computing represents a paradigm shift in computation, leveraging the principles of quantum mechanics to solve problems intractable for classical computers. This book provides a comprehensive exploration of quantum computing, encompassing its foundational concepts, architecture, algorithms, programming techniques, and real-world applications. Beginning with an overview and historical evolution, it delves into the fundamental differences between classical and quantum computing, highlighting key quantum mechanical phenomena such as superposition, entanglement, and interference. The book f
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37

Yang, Xin-She, and Slawomir Koziel. Computational Optimization, Methods and Algorithms. Springer, 2016.

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38

Slowik, Adam. Swarm Intelligence Algorithms. Taylor & Francis Group, 2022.

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39

Tan, Ying. Fireworks Algorithm: A Novel Swarm Intelligence Optimization Method. Springer, 2015.

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40

Tan, Ying. Fireworks Algorithm: A Novel Swarm Intelligence Optimization Method. Springer, 2015.

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41

Tan, Ying. Fireworks Algorithm: A Novel Swarm Intelligence Optimization Method. Springer, 2016.

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42

Kaipa, Krishnanand N., and Debasish Ghose. Glowworm Swarm Optimization: Theory, Algorithms, and Applications. Springer, 2017.

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43

Kaipa, Krishnanand N., and Debasish Ghose. Glowworm Swarm Optimization: Theory, Algorithms, and Applications. Springer, 2018.

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44

Slowik, Adam. Swarm Intelligence Algorithms: A Tutorial. Taylor & Francis Group, 2020.

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45

Swarm Intelligence Algorithms: A Tutorial. Taylor & Francis Group, 2020.

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46

Slowik, Adam. Swarm Intelligence Algorithms: A Tutorial. Taylor & Francis Group, 2020.

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47

Slowik, Adam. Swarm Intelligence Algorithms: A Tutorial. Taylor & Francis Group, 2020.

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48

Chen, Shengyong, Yujun Zheng, Xueqin Lu, and Minxia Zhang. Biogeography-Based Optimization: Algorithms and Applications. Springer, 2018.

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49

Chen, Shengyong, Yujun Zheng, Xueqin Lu, and Minxia Zhang. Biogeography-Based Optimization: Algorithms and Applications. Springer, 2018.

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50

Slowik, Adam. Swarm Intelligence Algorithms: Modifications and Applications. Taylor & Francis Group, 2020.

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