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Recent Algorithms and Applications in Swarm Intelligence Research

Book Description

Advancements in the nature-inspired swarm intelligence algorithms continue to be useful in solving complicated problems in nonlinear, non-differentiable, and un-continuous functions as well as being applied to solve real-world applications. Recent Algorithms and Applications in Swarm Intelligence Research highlights the current research on swarm intelligence algorithms and its applications. Including research and survey and application papers, this book serves as a platform for students and scholars interested in achieving their studies on swarm intelligence algorithms and their applications.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Associate Editors
    2. List of Reviewers
  5. Preface
    1. WHAT IS THE BOOK ABOUT?
    2. ORGANIZATION OF THE BOOK
  6. Acknowledgment
  7. Section 1: Swarm Intelligence Algorithms
    1. Chapter 1: Scatter Search and Path Relinking
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. PROBLEM FORMULATION
      4. 3. BRIEF SUMMARY OF PREVIOUS MINLA METHODS
      5. 4. SCATTER SEARCH METHODOLOGY
      6. 5. DIVERSIFICATION GENERATION METHODS
      7. 6. IMPROVEMENT METHOD
      8. 7. FILTERING SOLUTIONS
      9. 8. COMBINATION METHOD BASED ON PATH RELINKING
      10. 9. COMPUTATIONAL EXPERIMENTS
      11. 10. CONCLUSION
    2. Chapter 2: A Complementary Cyber Swarm Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. 3. COMPLEMENTARY VARIANT OF CYBER SWARM ALGORITHM
      5. 4. EXPERIMENTAL RESULTS AND ANALYSIS
      6. 5. CONCLUDING REMARKS
    3. Chapter 3: Path Relinking Scheme for the Max-Cut Problem within Global Equilibrium Search
      1. ABSTRACT
      2. PATH RELINKING SCHEME FOR THE MAX-CUT PROBLEM WITHIN GLOBAL EQUILIBRIUM SEARCH
      3. METHOD
      4. RESULTS
    4. Chapter 4: Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE PATH-RELINKING ALGORITHM
      4. 3. RESULTS AND DISCUSSION
      5. 4. CONCLUSION
    5. Chapter 5: A Multiobjective Particle Swarm Optimizer for Constrained Optimization
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE SURVEY
      4. 3. PROPOSED APPROACH
      5. 4. COMPARATIVE STUDY
      6. 5. CONCLUSION
    6. Chapter 6: Experimental Study on Boundary Constraint Handling in Particle Swarm Optimization
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. PARTICLE SWARM OPTIMIZATION
      4. 3. BOUNDARY CONSTRAINTS HANDLING
      5. 4. EXPERIMENTAL STUDY
      6. 5. POPULATION DIVERSITY ANALYSIS AND DISCUSSION
      7. 6. CONCLUSION
    7. Chapter 7: Chaos-Enhanced Firefly Algorithm with 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. CONCLUSION
    8. Chapter 8: 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. CONCLUSION
  8. Section 2: Swarm Intelligence Applications
    1. Chapter 9: Swarm Intelligence for Non-Negative Matrix Factorization
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LOW RANK APPROXIMATIONS
      4. 3. SWARM INTELLIGENCE OPTIMIZATION
      5. 4. IMPROVING NMF WITH SWARM INTELLIGENCE OPTIMIZATION
      6. 5. SETUP
      7. 6. EXPERIMENTAL EVALUATION
      8. 7. CONCLUSION
    2. Chapter 10: How Ants Can Efficiently Solve the Generalized Watchman Route Problem
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. PROBLEM STATEMENT
      5. ANT ALGORITHM FOR MOBOTS
      6. SIMULATION EXPERIMENT
      7. CONCLUSION
    3. Chapter 11: Image Segmentation Based on Bacterial Foraging and FCM Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. BRIEF DESCRIPTION OF FCM AND BFOA
      4. BF-FCM ALGORITHM
      5. IMAGE SEGMENTATION EXPERIMENTS
      6. CONCLUSIONS AND PERSPECTIVES
    4. Chapter 12: Minimum Span Frequency Assignment Based on a Multiagent Evolutionary Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. MATHEMATICAL MODEL FOR FAPS
      4. MULTIAGENT EVOLUTIONARY ALGORITHM FOR MSFAPS
      5. EXPERIMENTAL STUDY
      6. CONCLUSION
    5. Chapter 13: Design of Robust Approach for Failure Detection in Dynamic Control Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. PROBLEM FORMULATION
      4. PROPOSED MODIFIED HYBRID IMMUNE ALGORITHM
      5. ADAPTIVE STATE FEEDBACK OBSERVER CONTROLLER BASED ON MIMEA
      6. DESIGN OF ROBUST IFD SCHEME
      7. SIMULATION RESULTS
      8. CONCLUSION
    6. Chapter 14: Effects of Multi-Robot Team Formations on Distributed Area Coverage
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. MULTI-ROBOT DISTRIBUTED AREA COVERAGE
      5. ANALYSIS
      6. EXPERIMENTAL RESULTS
      7. CONCLUSION AND FUTURE WORK
  9. Compilation of References
  10. About the Contributors