Advances in Swarm Intelligence

1. Front Matter

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2. Novel Swarm-Based Search Methods

   1. Comparison of Different Cue-Based Swarm Aggregation Strategies

      • Farshad Arvin, Ali Emre Turgut, Nicola Bellotto, Shigang Yue

      Pages 1-8

   2. PHuNAC Model: Emergence of Crowd’s Swarm Behavior

      • Olfa Beltaief, Sameh El Hadouaj, Khaled Ghedira

      Pages 9-18

   3. A Unique Search Model for Optimization

      • A. S. Xie

      Pages 19-26

   4. Improve the 3-flip Neighborhood Local Search by Random Flat Move for the Set Covering Problem

      • Chao Gao, Thomas Weise, Jinlong Li

      Pages 27-35

   5. The Threat-Evading Actions of Animal Swarms without Active Defense Abilities

      • Qiang Sun, XiaoLong Liang, ZhongHai Yin, YaLi Wang

      Pages 36-43

   6. Approximate Muscle Guided Beam Search for Three-Index Assignment Problem

      • He Jiang, Shuwei Zhang, Zhilei Ren, Xiaochen Lai, Yong Piao

      Pages 44-52

3. Novel Optimization Algorithm

   1. Improving Enhanced Fireworks Algorithm with New Gaussian Explosion and Population Selection Strategies

      • Bei Zhang, Minxia Zhang, Yu-Jun Zheng

      Pages 53-63

   2. A Unified Matrix-Based Stochastic Optimization Algorithm

      • Xinchao Zhao, Junling Hao

      Pages 64-73

   3. Chaotic Fruit Fly Optimization Algorithm

      • Xiujuan Lei, Mingyu Du, Jin Xu, Ying Tan

      Pages 74-85

   4. A New Bio-inspired Algorithm: Chicken Swarm Optimization

      • Xianbing Meng, Yu Liu, Xiaozhi Gao, Hengzhen Zhang

      Pages 86-94

   5. A Population-Based Extremal Optimization Algorithm with Knowledge-Based Mutation

      • Junfeng Chen, Yingjuan Xie, Hua Chen

      Pages 95-102

   6. A New Magnetotactic Bacteria Optimization Algorithm Based on Moment Migration

      • Hongwei Mo, Lili Liu, Mengjiao Geng

      Pages 103-114

   7. A Magnetotactic Bacteria Algorithm Based on Power Spectrum for Optimization

      • Hongwei Mo, Lili Liu, Mengjiao Geng

      Pages 115-125

4. Particle Swarm Optimization

   1. A Proposal of PSO Particles’ Initialization for Costly Unconstrained Optimization Problems: ORTHOinit

      • Matteo Diez, Andrea Serani, Cecilia Leotardi, Emilio F. Campana, Daniele Peri, Umberto Iemma et al.

      Pages 126-133

   2. An Adaptive Particle Swarm Optimization within the Conceptual Framework of Computational Thinking

      • Bin Li, Xiao-lei Liang, Lin Yang

      Pages 134-141

   3. Topology Optimization of Particle Swarm Optimization

      • Fenglin Li, Jian Guo

      Pages 142-149

   4. Fully Learned Multi-swarm Particle Swarm Optimization

      • Ben Niu, Huali Huang, Bin Ye, Lijing Tan, Jane Jing Liang

      Pages 150-157

   5. Using Swarm Intelligence to Search for Circulant Partial Hadamard Matrices

      • Frederick Kin Hing Phoa, Yuan-Lung Lin, Tai-Chi Wang

      Pages 158-164

5. Ant Colony Optimization for Travelling Salesman Problem

   1. High Performance Ant Colony Optimizer (HPACO) for Travelling Salesman Problem (TSP)

      • Sudip Kumar Sahana, Aruna Jain

      Pages 165-172

This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.

• ant colony optimization
• augmented reality
• automated and humanized design
• evolutionary algorithms
• genetic algorithms
• hybrid model
• machine learning
• machine vision
• mathematical expression recognition and retrieval
• medical diagnosis
• neural networks
• optimization algorithms
• parallel metaheuristics
• quantum particle optimization
• reinforcement learning
• steganography
• swarm robotics
• watermarking
• algorithm analysis and problem complexity

• Key Laboratory of Machine Perception (MOE), Peking University, Beijing, China

  Ying Tan

• Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

  Yuhui Shi

• Computer Science Department, CINVESTAV-IPN, Mexico

  Carlos A. Coello Coello

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