
Nature-Inspired Computation in Navigation and Routing Problems by Xin-She Yang
This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.
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Applications of Ant Colony Optimization and its Variants
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Applications of Bat Algorithm and its Variants
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Applied Nature-Inspired Computing: Algorithms and Case Studies
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Frontiers in Genetics Algorithm Theory and Applications
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Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing
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Frontiers in Nature-Inspired Industrial Optimization
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Discrete Cuckoo Search for Combinatorial Optimization
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Applied Optimization and Swarm Intelligence
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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications
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Benchmarks and Hybrid Algorithms in Optimization and Applications
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Frontier Applications of Nature Inspired Computation
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Applications of Firefly Algorithm and its Variants
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Applications of Flower Pollination Algorithm and its Variants
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Nature-Inspired Computing for Smart Application Design
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Optimizing Solutions for Real-Life Problems
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Engineering Applications of AI and Swarm Intelligence
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Advancements in Optimization and Nature-Inspired Computing for Solutions in Contemporary Engineering Challenges
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Applied Multi-objective Optimization
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Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance
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Solving with Bees
Dr. Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford, then worked at Cambridge University and UK's National Physical Laboratory as a Senior Research Scientist. Now he Reader in modelling and optimization at Middlesex University London. He is also the IEEE CIS task force chair for business intelligence and knowledge management. With more than 250 research publications and 25 books, he has named as a highly cited researcher by Clarivate Analytics (formerly Thomson Reuters Web of Science) for four consecutive years (2016, 2017, 2018 and 2019). His main research interests include computational intelligence, nature-inspired computing, applied mathematics, machine learning, modelling and simulation as well as data mining.
Prof. Yu-Xin Zhao received his Ph.D. degree in Navigation, Guidance, and Control from Harbin Engineering University (HEU) in 2005 and completed postdoctoral research in Control Science and Engineering at Harbin Institute of Technology (HIT) in 2008. He is currently the Dean and a Professor at the College of Automation, Harbin Engineering University. His research interests include artificial intelligence, filtering theory, navigation theory and application, as well as intelligent transportation systems. He has published more than 100 papers, including more than 40 international journal papers in these areas. He also has 18 national patents. Dr. Zhao has won numerous awards, including the Young ChangJiang Scholar (2018) and LongJiang Scholar. He has served the academic community in various capacities, including Fellow of IET, senior member of IEEE, a member of the Royal Institute of Navigation, and a Fellow of China Navigation Institute.
| SKU | Unavailable |
| ISBN 13 | 9789811518416 |
| ISBN 10 | 9811518416 |
| Title | Nature-Inspired Computation in Navigation and Routing Problems |
| Author | Xin She Yang |
| Series | Springer Tracts In Nature-Inspired Computing |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer Verlag, Singapore |
| Year published | 2020-02-20 |
| Number of pages | 222 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |



















