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Emerging Research on Swarm Intelligence and Algorithm Optimization

Book Description

Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence. Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
  6. Preface
    1. WHAT IS THE BOOK ABOUT?
    2. ORGANIZATION OF THE BOOK
  7. Acknowledgment
  8. Section 1: Swarm Intelligence Algorithms
    1. Chapter 1: An Optimization Algorithm Based on Brainstorming Process
      1. ABSTRACT
      2. INTRODUCTION
      3. BRAINSTORMING PROCESS
      4. MODELING BRAINSTORMING PROCESS
      5. BRAIN STORM OPTIMIZATION ALGORITHM
      6. EXPERIMENTS AND DISCUSSIONS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. ADDITIONAL READING
      12. KEY TERMS AND DEFINITIONS
    2. Chapter 2: Analysis of Firefly Algorithms and Automatic Parameter Tuning
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. FIREFLY ALGORITHM
      4. 3. CHAOS-ENHANCED FA
      5. 4. AUTOMATIC PARAMETER TUNING
      6. 5. NUMERICAL EXPERIMENTS
      7. 6. DESIGN OPTIMIZATION
      8. 7. FUTURE RESEARCH DIRECTIONS
      9. 8. CONCLUSION
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
    3. Chapter 3: A Complementary Cyber Swarm Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. 2. PSO LITERATURE REVIEW
      4. 3. COMPLEMENTARY VARIANT OF CYBER SWARM ALGORITHM
      5. 4. EXPERIMENTAL RESULTS AND ANALYSIS
      6. 5. CONCLUDING REMARKS
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    4. Chapter 4: Population Diversity of Particle Swarm Optimizer Solving Single- and Multi-Objective Problems
      1. ABSTRACT
      2. INTRODUCTION
      3. PRELIMINARIES
      4. POPULATION DIVERSITY
      5. EXPERIMENTAL STUDY
      6. ANALYSIS AND DISCUSSION
      7. DISCUSSIONS
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
    5. Chapter 5: Experimental Study on Boundary Constraints Handling in Particle Swarm Optimization from a Population Diversity Perspective
      1. ABSTRACT
      2. INTRODUCTION
      3. PARTICLE SWARM OPTIMIZATION
      4. BOUNDARY CONSTRAINTS HANDLING
      5. EXPERIMENTAL STUDY
      6. CONCLUSION
      7. ACKNOWLEDGMENT
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    6. Chapter 6: A Particle Swarm Optimizer for Constrained Multiobjective Optimization
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE SURVEY
      4. PROPOSED APPROACH
      5. COMPARATIVE STUDY
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. ADDITIONAL READING
      10. KEY TERMS AND DEFINITIONS
  9. Section 2: Swarm Intelligence Applications
    1. Chapter 7: Hybrid Swarm Intelligence-Based Biclustering Approach for Recommendation of Web Pages
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. METHODS AND MATERIALS
      5. PROPOSED WORK
      6. EXPERIMENTAL ANALYSIS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    2. Chapter 8: Optimization of Drilling Process via Weightless Swarm Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. THE FORMULATION OF OPTIMIZATION PROBLEM
      4. WEIGHTLESS SWARM ALGORITHM
      5. PARAMETER SENSITIVITY ANALYSIS (PSA)
      6. RESULTS AND COMPARISON
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 9: Artificial Insect Algorithms for Routing in Wireless Sensor Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. ARTIFICIAL INSECT-BASED ROUTING ALGORITHMS IN WSN
      4. SIMULATING THE BEHAVIOR OF TERMITES
      5. THE TERMITE-HILL ROUTING ALGORITHM
      6. PERFORMANCE EVALUATION
      7. CONCLUSION AND FUTURE WORKS
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    4. Chapter 10: Coverage Path Planning Using Mobile Robot Team Formations
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MULTI-ROBOT DISTRIBUTED AREA COVERAGE
      5. ANALYSIS
      6. EXPERIMENTAL RESULTS
      7. FUTURE DIRECTION: BEYOND FIXED ROBOT TEAMS WITH DYNAMIC FORMATION MAINTENANCE FOR AREA COVERAGE
      8. CONCLUSION AND FUTURE WORK
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. ADDITIONAL READING
      12. KEY TERMS AND DEFINITIONS
    5. Chapter 11: Path Relinking Scheme for the Max-Cut Problem
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PATH RELINKING AND GLOBAL EQUILIBRIUM SEARCH
      5. COMPUTATIONAL STUDY
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    6. Chapter 12: Image Segmentation Based on Bio-Inspired Optimization Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. IMAGE SEGMENTATION AND FCM
      5. BIO-INSPIRED OPTIMIZATION ALGORITHMS
      6. IMAGE SEGMENTATION EXPERIMENTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. ADDITIONAL READING
      12. KEY TERMS AND DEFINITIONS
    7. Chapter 13: Swarm Intelligence for Dimensionality Reduction
      1. ABSTRACT
      2. INTRODUCTION
      3. LOW RANK APPROXIMATIONS
      4. SWARM INTELLIGENCE OPTIMIZATION
      5. IMPROVING NMF WITH SWARM INTELLIGENCE OPTIMIZATION
      6. SETUP
      7. EXPERIMENTAL EVALUATION
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
  10. Compilation of References
  11. About the Contributors