Advances in Swarm Intelligence 10th International Conference, ICSI 2019, Chiang Mai, Thailand, July 26-30, 2019, Proceedings, Part I

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Main Authors Tan, Ying, Shi, Yuhui, Niu, Ben
Format eBook Conference Proceeding
LanguageEnglish
Published Cham Springer International Publishing AG 2019
Springer International Publishing
Edition1
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN9783030263683
3030263681
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-26369-0

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Author 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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  organization: Cornell University, Ithaca, USA
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  organization: Purdue University, West Lafayette, USA
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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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Volume 11655
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