Advances in Swarm Intelligence 10th International Conference, ICSI 2019, Chiang Mai, Thailand, July 26-30, 2019, Proceedings, Part I
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| Format | eBook Conference Proceeding |
| Language | English |
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Cham
Springer International Publishing AG
2019
Springer International Publishing |
| Edition | 1 |
| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9783030263683 3030263681 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-030-26369-0 |
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| Author | Tan, Ying Niu, Ben Shi, Yuhui |
|---|---|
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| DOI | 10.1007/978-3-030-26369-0 |
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| Editor | Tan, Ying Niu, Ben Shi, Yuhui |
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| RelatedPersons | Hartmanis, Juris Gao, Wen Bertino, Elisa Woeginger, Gerhard Goos, Gerhard Steffen, Bernhard Yung, Moti |
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| SubjectTerms | Algorithm Analysis and Problem Complexity Arithmetic and Logic Structures Artificial Intelligence Computer Communication Networks Computer Science Computer software Information Systems Applications (incl. Internet) |
| Subtitle | 10th International Conference, ICSI 2019, Chiang Mai, Thailand, July 26-30, 2019, Proceedings, Part I |
| TableOfContents | 4 Conclusions and Future Work -- References -- Population-Based Metaheuristics for Planning Interval Training Sessions in Mountain Biking -- 1 Introduction -- 2 Fundamentals of Interval Training in Mountain Bike -- 3 Problem Definition and Proposed Solution Method -- 3.1 Problem Definition -- 3.2 Algorithm for Planning the Interval Training -- 4 Experiments and Results -- 4.1 Scenario A -- 4.2 Scenario B -- 5 Conclusion -- References -- Comparison of Infrastructure and AdHoc Modes in Survivable Networks Enabled by Evolutionary Swarms -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 The Agents -- 3.2 The Optimization Method -- 4 Experiments and Results -- 4.1 Experimental Setup -- 4.2 Discussion of Results -- 5 Conclusion -- References -- Particle Swarm Optimization -- An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm -- 1 Introduction -- 2 Background -- 2.1 Particle Swarm Optimization -- 2.2 Formalized Control Parameter Tuning -- 2.3 Automated Control Parameter Tuning Methods -- 2.4 fANOVA -- 3 Experimental Setup -- 4 Results -- 4.1 Variance in Fitness -- 4.2 Response Surface Analysis -- 5 Conclusions -- References -- Parameters Optimization of Relay Self-oscillations Sampled Data Controller Based on Particle Swarm Optimization -- Abstract -- 1 Introduction -- 2 Mathematical Description of System Under Investigation -- 3 Periodical Movements in the Discrete Relay System -- 4 Stability of Self-oscillation in the Digital Relay System and Linearization -- 4.1 Linearization of Relay Sampled-Data Feedback Systems -- 5 Optimization of RCS with Use PSO Method -- 6 Example -- 7 Conclusion -- Acknowledgement -- References -- Niching Particle Swarm Optimizer with Entropy-Based Exploration Strategy for Global Optimization -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Modified Updating Strategies 2.2 Parameter Control Strategies -- 2.3 Hybridization with Other Techniques -- 3 Proposed Algorithm -- 3.1 Exploitation Operator -- 3.2 Exploration Operator -- 4 Experiments and Discussions -- 4.1 Experiments Settings -- 4.2 Results and Discussions -- 5 Conclusions -- Acknowledgments -- References -- A Study on Designing an Aperiodic Antenna Array Using Boolean PSO -- 1 Introduction -- 1.1 Antenna Arrays -- 1.2 Particle Swarm Optimization -- 2 Setup of Computer Simulation -- 2.1 Encoding -- 2.2 Fitness Function -- 2.3 Algorithm for Computer Simulation -- 3 Simulation Setup and Results -- 4 Conclusion -- References -- Building Energy Performance Optimization: A New Multi-objective Particle Swarm Method -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Multi-objective Optimization -- 2.2 Particle Swarm Optimization -- 3 The Proposed PSO-Based Multi-objective Approach -- 3.1 Multi-objective Optimization Model of Building Energy Performance -- 3.2 The Improved Bare-Bones Multi-objective PSO Algorithm -- 4 Experiments and Analyses -- 4.1 Application Cases -- 4.2 Comparison Algorithm and Performance Index -- 4.3 Comparison with NSGA-II, MOABC and MOPSO -- 5 Conclusions -- Acknowledgments -- References -- A Novel PSOEDE Algorithm for Vehicle Scheduling Problem in Public Transportation -- Abstract -- 1 Introduction -- 2 Vehicle Scheduling Problem -- 3 The Proposed PSOEDE Algorithm -- 3.1 PSO Operator in Mutation Step -- 3.2 Ensemble Strategy of Random Parameters -- 4 Simulation Test and Discussion -- 4.1 Parameters Setting and Encoding -- 4.2 Experiment Results and Discussion -- 5 Conclusion -- Acknowledgements -- References -- Hierarchical Competition Framework for Particle Swarm Optimization -- 1 Introduction -- 2 Canonical Particle Swarm Optimizer and Quantum-Behaved Particle Swarm Optimizer -- 2.1 Canonical Particle Swarm Optmizer 3.1 Weight-Based Guiding Strategy 4 Conclusions -- Acknowledgments -- References -- Physarum-Based Ant Colony Optimization for Graph Coloring Problem -- 1 Introduction -- 2 Related Works -- 3 Physarum-Based Ant Colony Optimization -- 3.1 The Physarum Mathematical Model -- 3.2 The Physarum-Based Ant Colony Optimization -- 4 Experiments -- 4.1 Datasets -- 4.2 Efficiency -- 4.3 Stability -- 4.4 Computational Cost -- 5 Conclusion -- References -- Ant Colony Algorithm Based Scheduling with Lot-Sizing for Printed Circuit Board Assembly Shop -- Abstract -- 1 Introduction -- 2 Problem Statement -- 3 Ant Colony Algorithm with Lot-Sizing -- 3.1 Two-Stage Structure and Algorithm Flow Chart -- 3.2 Job Sequencing -- 3.3 Batch Scheduling and Lot-Sizing -- 3.4 Local Search Strategy -- 4 Computational Results -- 4.1 Parameters Setting -- 4.2 Convergence Validation -- 4.3 Comparisons with Other Heuristics -- 5 Conclusions -- References -- Variable Speed Robot Navigation by an ACO Approach -- Abstract -- 1 Introduction -- 2 ACO Algorithms for Robot Path Planning -- 3 Variable Speed Navigation and Map Building -- 4 Simulation and Comparison Studies -- 4.1 Comparison of the Proposed Variable Speed Model with GA-ACO Algorithm -- 4.2 Comparison of the Variable Speed ACO with Others -- 5 Conclusion -- References -- Solving Scheduling Problems in PCB Assembly and Its Optimization Using ACO -- Abstract -- 1 Introduction -- 1.1 PCB Assembly -- 2 Literature Review -- 3 Ant Colony Optimization -- 3.1 Assumption -- 4 An ACO Algorithm for PCB Grouping -- 4.1 ACO Algorithm for PCB Group Sequencing -- 5 Validation -- 6 Results and Comparisons -- 7 Conclusion -- References -- Fireworks Algorithms and Brain Storm Optimization -- Accelerating Fireworks Algorithm with Weight-Based Guiding Sparks -- 1 Introduction -- 2 Optimization Mechanisms of Fireworks Algorithm -- 3 Two Proposed Strategies for GFWA Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Novel Models and Algorithms for Optimization -- Generative Adversarial Optimization -- 1 Introduction -- 2 Related Works -- 2.1 Meta-heuristic Algorithms -- 2.2 Generative Adversarial Networks -- 3 GAO: Generative Adversarial Optimization -- 3.1 Model Architectures -- 3.2 Training of GAO -- 4 Experiments -- 5 Conclusion -- References -- Digital Model of Swarm Unit System with Interruptions -- Abstract -- 1 Introduction -- 2 Models of Interruption System Components -- 3 Sampling of Time Densities -- 4 The United Model of the System with Interruptions -- 5 The Digital Competition -- 6 Conclusion -- References -- Algorithm Integration Behavior for Discovering Group Membership Rules -- Abstract -- 1 Introduction -- 2 Theoretical Review -- 2.1 Information Exploitation Process -- 2.2 Domain Classification by Complexity -- 3 Method -- 4 Results -- 5 Conclusions -- References -- Success-History Based Position Adaptation in Co-operation of Biology Related Algorithms -- Abstract -- 1 Introduction -- 2 Fuzzy-Controlled COBRA -- 3 Proposed Modification -- 4 Experimental Results -- 5 Conclusions -- Acknowledgments -- References -- An Inter-Peer Communication Mechanism Based Water Cycle Algorithm -- Abstract -- 1 Introduction -- 2 Water Cycle Algorithms -- 3 Inter-Peer Communication Mechanism Based Water Cycle Algorithm -- 4 Experiments and Analysis -- 4.1 Benchmark Functions Parameter Settings -- 4.2 Experimental Results -- 5 Conclusions and Future Work -- Acknowledgements -- References -- Cooperation-Based Gene Regulatory Network for Target Entrapment*-12pt -- 1 Introduction -- 2 The Proposed Framework -- 2.1 Overall Structure -- 2.2 Cooperation with Partners -- 2.3 Self-organizing Obstacle Avoidance Mechanism -- 3 Experimental Analysis -- 3.1 Entrapping Stationary Targets 2.2 Quantum-Behaved Particle Swarm Optimize -- 3 Hierarchical Competition Framework Based PSO Algorithm -- 3.1 Combined with Canonical PSO -- 3.2 Combined with QPSO -- 4 Experiments -- 4.1 Database Summary and Parameters Set -- 4.2 Results and Analysis -- 5 Conclusion -- References -- Study on Method of Cutting Trajectory Planning Based on Improved Particle Swarm Optimization for Roadheader -- Abstract -- 1 Introduction -- 2 The Principle of Basic PSO -- 3 Cutting Trajectory Planning Based on Improved PSO -- 4 Simulation and Results -- 5 Conclusion -- Acknowledgements -- References -- Variants and Parameters Investigations of Particle Swarm Optimisation for Solving Course Timetabling Problems -- Abstract -- 1 Introduction -- 2 Particle Swarm Optimisation (PSO) -- 3 University Course Timetabling Problem (UCTP) -- 4 Particle Swarm Optimisation Based Timetabling (PSOT) Tool -- 5 Experimental Results and Analysis -- 5.1 PSO Parameters Investigation -- 5.2 Performance of PSO's Variants -- 6 Conclusions -- Acknowledgements -- References -- Ant Colony Optimization -- Multiple Start Modifications of Ant Colony Algorithm for Multiversion Software Design -- Abstract -- 1 Introduction -- 2 The Problem of Designing Multiversion Software Systems -- 3 Architecture of the Designed Software -- 4 Modification of the Ant Algorithm for Descending Design -- 5 Modification of the Ant Algorithm for Upstream Design -- 6 Software Implementation -- 7 Method of Multiple Algorithm Start -- 8 Simulation Results -- 9 Conclusion -- Acknowledgments -- References -- Ant Colony Algorithm for Cell Tracking Based on Gaussian Cloud Model -- Abstract -- 1 Introduction -- 2 The Algorithm -- 2.1 Gaussian Cloud Model -- 2.2 Algorithm Description -- 2.2.1 Initialization of the Algorithm -- 2.2.2 Movement of the Ants -- 2.2.3 Pheromone Updating -- 2.2.4 Algorithm Structure -- 3 Experiments |
| Title | Advances in Swarm Intelligence |
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