Swarm Intelligence: Concepts, Models, and Applications

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  • Topic: Optimization, Swarm intelligence, Particle swarm optimization
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Swarm Intelligence: Concepts, Models and Applications
Technical Report 2012-585

Hazem Ahmed Janice Glasgow

School of Computing Queen's University Kingston, Ontario, Canada K7L3N6 {hazem, janice}@cs.queensu.ca

February 2012

Report Index
1. 2.

Introduction ........................................................................................................................ 2 Swarm Intelligence (SI) Models ......................................................................................... 4 2.1 Ant Colony Optimization (ACO) Model ........................................................................ 4 2.1.1 Ants in Nature................................................................................................................ 4 2.1.1.1 Ants Stigmergic behaviour .................................................................................................... 4 2.1.1.2 The Double Bridge Experiment ............................................................................................. 5 2.1.1.3 Real Ants vs. Artificial Ants.................................................................................................. 8

2.1.2 Ant Colony Optimization Metaheuristic ....................................................................... 9 2.1.2.1 ACO Example: Traveling Salesman Problem and Ant System ............................................12 2.1.2.2 ACO Variations: Ant System and its Extensions .................................................................14 2.1.2.3 ACO Discussion ...................................................................................................................15

2.2 Particle Swarm Optimization (PSO) Model ............................................................ 16 2.2.1 Birds in Nature ............................................................................................................ 16 2.2.1.1 Birds Flocking Behaviour .....................................................................................................16 2.2.1.2 Birds‘ Physical Movement vs. Humans‘ Psychological Change ..........................................18

2.2.2 Particle Swarm Optimization Metaheuristic............................................................... 18 2.2.2.1 The Original PSO Algorithm ................................................................................................19 2.2.2.2 The Refinements and Extensions to the Original PSO .........................................................22 2.2.2.3 PSO Discussion ....................................................................................................................27

3.

SI Applications .................................................................................................................... 31 3.1 ACO Applications ...................................................................................................... 31 3.1.1 ACO Relevance to Bioinformatics .............................................................................. 32

3.2 PSO Applications ...................................................................................................... 32 3.2.1 PSO Relevance to Bioinformatics ............................................................................... 33 4.

Summary and Concluding Remarks ................................................................................. 34 4.1 SI General Advantages ........................................................................................................ 34 4.2 SI General Limitations ........................................................................................................ 34 4.3 Comparison between the two discussed SI Models: ACO vs. PSO .................................... 35 4.4 Other SI Models .................................................................................................................. 36 4.5 Concluding Remarks and Open Questions...
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