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PSO_0.3-1.bin
  • Classification:Numerical Algorithm-Artificial Intelligence - matlab
  • Development Tool:matlab
  • Sise:135 KB
  • Upload time:2014/6/16 5:23:58
  • Uploader:saeed__2
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Description
This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member of this particle swarm could be a solution of the optimization problem. This swarm flies in the search field (of D dimensions) and each member of it is attracted by its personal best solution and by the best solution of its neighbours. Each particle has a memory storing all data relating to its flight (location, speed and its personal best solution). It can also inform its neighbours, i.e. communicate its speed and position. This ability is known as socialisation. For each iteration, the objective function is evaluated for every member of the swarm. Then the leader of the whole swarm can be determined: it is the particle with the best personal solution. The process leads at the end to the best global solution.




File list:
PSO_0.3
......\.svn
......\....\prop-base
......\....\.........\builder.sce.svn-base
......\....\.........\changelog.txt.svn-base
......\....\.........\license.txt.svn-base
......\....\.........\readme.txt.svn-base
......\....\props
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......\....\.........\builder.sce.svn-base
......\....\.........\changelog.txt.svn-base
......\....\.........\license.txt.svn-base
......\....\.........\readme.txt.svn-base
......\....\tmp
......\....\...\prop-base
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......\....\...\text-base
......\....\all-wcprops
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......\.....\.svn
......\.....\....\prop-base
......\.....\....\props
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......\.....\....\entries
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......\...\.svn
......\...\....\prop-base
......\...\....\.........\PSO.quit.svn-base
......\...\....\.........\PSO.start.svn-base
......\...\....\props
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......\...\....\.........\PSO.quit.svn-base
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......\...\....\tmp
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......\...\....\dir-prop-base
......\...\....\entries
......\...\PSO.quit
......\...\PSO.start
......\jar
......\...\scilab_en_US_help.jar
......\macros
......\......\.svn
......\......\....\prop-base
......\......\....\.........\buildmacros.sce.svn-base
......\......\....\.........\cleanmacros.sce.svn-base
......\......\....\.........\PSO_bsg_starcraft.sci.svn-base
......\......\....\.........\PSO_bsg_starcraft_radius.sci.svn-base
......\......\....\.........\PSO_inertial.sci.svn-base
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......\......\....\.........\PSO_bsg_starcraft.sci.svn-base
......\......\....\.........\PSO_bsg_starcraft_radius.sci.svn-base
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......\......\....\.........\PSO_inertial_radius.sci.svn-base
......\......\....\tmp
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......\......\....\...\props
......\......\....\...\text-base
......\......\....\all-wcprops
......\......\....\dir-prop-base
......\......\....\entries
......\......\buildmacros.sce
......\......\cleanmacros.sce
......\......\names
......\......\PSO_bsg_starcraft.bin
......\......\PSO_bsg_starcraft.sci
......\......\PSO_bsg_starcraft_radius.bin
......\......\PSO_bsg_starcraft_radius.sci
......\......\PSO_inertial.bin
......\......\PSO_inertial.sci
......\......\PSO_inertial_radius.bin
......\......\PSO_inertial_radius.sci
......\tests
......\.....\.svn
......\.....\....\prop-base
......\.....\....\props
......\.....\....\text-base
......\.....\....\tmp
......\.....\....\...\prop-base
......\.....\....\...\props
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......\.....\....\all-wcprops
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......\.....\unit_tests
......\.....\..........\.svn
......\.....\..........\....\prop-base
......\.....\..........\....\props
......\.....\..........\....\text-base
......\.....\..........\....\.........\objective.sce.svn-base
......\.....\..........\....\.........\PSO_bsg_starcraft.dia.ref.svn-base
......\.....\..........\....\.........\PSO_bsg_starcraft.tst.svn-base
......\.....\..........\....\.........\PSO_bsg_starcraft_radius.tst.svn-base
......\.....\..........\....\.........\PSO_inertial.tst.svn-base
......\.....\..........\....\.........\PSO_inertial_radius.tst.svn-base
......\.....\..........\....\tmp
......\.....\..........\....\...\prop-base
......\.....\..........\....\...\props
......\.....\..........\....\...\text-base
......\.....\..........\....\all-wcprops
......\.....\..........\....\entries
......\.....\..........\objective.sce
......\.....\..........\PSO_bsg_starcraft.dia.ref
......\.....\..........\PSO_bsg_starcraft.tst
......\.....\..........\PSO_bsg_starcraft_radius.tst
......\.....\..........\PSO_inertial.tst
......\.....\..........\PSO_inertial_radius.tst
......\changelog.txt
......\DESCRIPTION
......\FILES
......\license.txt
......\loader.sce
......\readme.txt
Related source code
[PSO-0.3-1-src] - This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member of this particle swarm could be a solution of the optimization problem. This swarm flies in the search field (of D dimensions) and each member of it is attracted by its personal best solution and by the best solution of its neighbours. Each particle has a memory storing all data relating to its flight (location, speed and its personal best solution). It can also inform its neighbours, i.e. communicate its speed and position. This ability is known as socialisation. For each iteration, the objective function is evaluated for every member of the swarm. Then the leader of the whole swarm can be determined: it is the particle with the best personal solution. The process leads at the end to the best global solution.
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