https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&feed=atom&action=history
Particle Swarm Optimization - Scholarpedia Draft - Revision history
2024-03-29T09:47:24Z
Revision history for this page on the wiki
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https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4939&oldid=prev
Mmontes at 16:51, 7 November 2008
2008-11-07T16:51:43Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:51, 7 November 2008</td>
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<td colspan="2" class="diff-lineno">Line 48:</td>
<td colspan="2" class="diff-lineno">Line 48:</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== The algorithm ===</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== The algorithm ===</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The PSO algorithm starts with the random generation of the particles' positions within an initialization region </div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The PSO algorithm starts with the random generation of the particles' positions within an initialization region </div></td>
</tr>
<tr>
<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><math>\Theta^\prime \subseteq \Theta</math>. Velocities are usually initialized within <math>\Theta^\prime</math> but they can also be initialized to zero or to small random values to prevent <del class="diffchange diffchange-inline">particles</del> <del class="diffchange diffchange-inline">to leave</del> the search space during the first iterations. During the main loop of the algorithm, the particles' velocities and positions are iteratively updated until a stopping criterion is met. </div></td>
<td class="diff-marker">+</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><math>\Theta^\prime \subseteq \Theta</math>. Velocities are usually initialized within <math>\Theta^\prime</math> but they can also be initialized to zero or to small random values to prevent <ins class="diffchange diffchange-inline">them</ins> <ins class="diffchange diffchange-inline">leaving</ins> the search space during the first iterations. During the main loop of the algorithm, the particles' velocities and positions are iteratively updated until a stopping criterion is met. </div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The update rules are:</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The update rules are:</div></td>
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</table>
Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4938&oldid=prev
Mmontes at 16:44, 7 November 2008
2008-11-07T16:44:23Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:44, 7 November 2008</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== The algorithm ===</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>=== The algorithm ===</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The PSO algorithm starts with the random generation of the particles' positions within an initialization region </div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The PSO algorithm starts with the random generation of the particles' positions within an initialization region </div></td>
</tr>
<tr>
<td colspan="2" class="diff-empty"> </td>
<td class="diff-marker">+</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><math>\Theta^\prime \subseteq \Theta</math>. Velocities are usually initialized within <math>\Theta^\prime</math> but they can also be initialized to zero or to small random values to prevent particles to leave the search space during the first iterations. During the main loop of the algorithm, the particles' velocities and positions are iteratively updated until a stopping criterion is met. </div></td>
</tr>
<tr>
<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><math>\Theta^\prime \subseteq \Theta</math>. Velocities are usually</div></td>
<td colspan="2" class="diff-empty"> </td>
</tr>
<tr>
<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>initialized to zero, but can be initialized to small random values. During the main loop of the algorithm, the particles' velocities and positions </div></td>
<td colspan="2" class="diff-empty"> </td>
</tr>
<tr>
<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>are iteratively updated until a stopping criterion is met. </div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The update rules are:</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The update rules are:</div></td>
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</table>
Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4935&oldid=prev
Mmontes at 16:33, 7 November 2008
2008-11-07T16:33:39Z
<p></p>
<table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:33, 7 November 2008</td>
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<td colspan="2" class="diff-lineno">Line 78:</td>
<td colspan="2" class="diff-lineno">Line 78:</td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>neighbors. It represents a group norm or standard that should be attained.</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>neighbors. It represents a group norm or standard that should be attained.</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In some cases, particles can be attracted to regions outside the feasible search space <del class="diffchange diffchange-inline">$</del>\Theta<del class="diffchange diffchange-inline">$</del>. For this reason, mechanisms for preserving solution feasibility and a proper swarm operation have been devised (Engelbrecht 2005). One of the least disruptive mechanisms for handling constraints is one in which particles going outside <del class="diffchange diffchange-inline">$</del>\Theta<del class="diffchange diffchange-inline">$</del> are not allowed to improve their personal best position so that they are attracted back to the feasible space in subsequent iterations.</div></td>
<td class="diff-marker">+</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>In some cases, particles can be attracted to regions outside the feasible search space <ins class="diffchange diffchange-inline"><math></ins>\Theta<ins class="diffchange diffchange-inline"></math></ins>. For this reason, mechanisms for preserving solution feasibility and a proper swarm operation have been devised (Engelbrecht 2005). One of the least disruptive mechanisms for handling constraints is one in which particles going outside <ins class="diffchange diffchange-inline"><math></ins>\Theta<ins class="diffchange diffchange-inline"></math></ins> are not allowed to improve their personal best position so that they are attracted back to the feasible space in subsequent iterations.</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A pseudocode version of the standard PSO algorithm is shown below:</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A pseudocode version of the standard PSO algorithm is shown below:</div></td>
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</table>
Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4934&oldid=prev
Mmontes: /* The algorithm */
2008-11-07T16:09:20Z
<p><span dir="auto"><span class="autocomment">The algorithm</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 16:09, 7 November 2008</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>any particle in the neighborhood of particle <math>p_i</math>, that is,</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>any particle in the neighborhood of particle <math>p_i</math>, that is,</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math>f(\vec{l}^{\,t}_i) \leq f(\vec{b}^{\,t}_j) \,\,\, \forall p_j \in</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math>f(\vec{l}^{\,t}_i) \leq f(\vec{b}^{\,t}_j) \,\,\, \forall p_j \in</div></td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>\mathcal{N}_i</math>. Alternatively, the neighborhood best can be selected as</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>the current best particle, that is, <math>f(\vec{l}^{\,t}_i) \leq f(\vec{x}^{\,t}_j) \,\,\, \forall p_j \in</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\mathcal{N}_i</math>. If the values of <math>w</math>, <math>\varphi_1</math> and <math>\varphi_2</math> are properly chosen, it is guaranteed that the particles' velocities do not grow to infinity (Clerc and Kennedy 2002).</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\mathcal{N}_i</math>. If the values of <math>w</math>, <math>\varphi_1</math> and <math>\varphi_2</math> are properly chosen, it is guaranteed that the particles' velocities do not grow to infinity (Clerc and Kennedy 2002).</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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</table>
Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4933&oldid=prev
Mmontes: /* History */
2008-11-07T15:20:08Z
<p><span dir="auto"><span class="autocomment">History</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 15:20, 7 November 2008</td>
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<td colspan="2" class="diff-lineno">Line 13:</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>their movement is governed by a set of rules. Some years later, Reynolds (1987) used a particle system to simulate the collective behavior of a flock of birds. In a similar kind of simulation, Heppner and Grenander (1990) included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>their movement is governed by a set of rules. Some years later, Reynolds (1987) used a particle system to simulate the collective behavior of a flock of birds. In a similar kind of simulation, Heppner and Grenander (1990) included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
</tr>
<tr>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research, in particular the dynamic theory of social impact (Nowak, Szamrej & Latané, 1990<del class="diffchange diffchange-inline">; Kennedy, 2006</del>), was another source of inspiration in the development of the first particle swarm optimization algorithm. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).</div></td>
<td class="diff-marker">+</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research, in particular the dynamic theory of social impact (Nowak, Szamrej & Latané, 1990), was another source of inspiration in the development of the first particle swarm optimization algorithm<ins class="diffchange diffchange-inline"> (Kennedy, 2006)</ins>. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).</div></td>
</tr>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
</tr>
</table>
Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4932&oldid=prev
Mmontes: /* References */
2008-11-07T15:18:43Z
<p><span dir="auto"><span class="autocomment">References</span></span></p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Bare bones particle swarms. In ''Proceedings of the IEEE Swarm Intelligence Symposium'', pages 80-87, IEEE Press, Piscataway, NJ, 2003.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Bare bones particle swarms. In ''Proceedings of the IEEE Swarm Intelligence Symposium'', pages 80-87, IEEE Press, Piscataway, NJ, 2003.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Swarm Intelligence. In ''Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies'' <del class="diffchange diffchange-inline">Zomaya, Albert</del> Y. (Ed.) , pages 187-219, Springer US, Secaucus, NJ, 2006.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Swarm Intelligence. In ''Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies''<ins class="diffchange diffchange-inline">.</ins> <ins class="diffchange diffchange-inline">A.</ins> Y.<ins class="diffchange diffchange-inline"> Zomaya</ins> (Ed.) , pages 187-219, Springer US, Secaucus, NJ, 2006.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy and R. Eberhart. Particle swarm optimization. In ''Proceedings of IEEE International Conference on Neural Networks'', pages 1942-1948, IEEE Press, Piscataway, NJ, 1995.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy and R. Eberhart. Particle swarm optimization. In ''Proceedings of IEEE International Conference on Neural Networks'', pages 1942-1948, IEEE Press, Piscataway, NJ, 1995.</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>R. Mendes, J. Kennedy, and J. Neves. The fully informed particle swarm:</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>simpler, maybe better. ''IEEE Transactions on Evolutionary Computation'', 8(3):204-210, 2004.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>simpler, maybe better. ''IEEE Transactions on Evolutionary Computation'', 8(3):204-210, 2004.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>A. Nowak, J. Szamrej, and B. Latané. From Private Attitude to Public Opinion: A Dynamic Theory of Social Impact. ''Psychological Review'', 97(3):362-376, 1990.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>R. Poli. Analysis of the publications on the applications of particle swarm</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>R. Poli. Analysis of the publications on the applications of particle swarm</div></td>
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Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4931&oldid=prev
Mmontes: /* References */
2008-11-07T15:14:17Z
<p><span dir="auto"><span class="autocomment">References</span></span></p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Bare bones particle swarms. In ''Proceedings of the IEEE Swarm Intelligence Symposium'', pages 80-87, IEEE Press, Piscataway, NJ, 2003.</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Bare bones particle swarms. In ''Proceedings of the IEEE Swarm Intelligence Symposium'', pages 80-87, IEEE Press, Piscataway, NJ, 2003.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy. Swarm Intelligence. In ''Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies'' Zomaya, Albert Y. (Ed.) , pages 187-219, Springer US, Secaucus, NJ, 2006.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy and R. Eberhart. Particle swarm optimization. In ''Proceedings of IEEE International Conference on Neural Networks'', pages 1942-1948, IEEE Press, Piscataway, NJ, 1995.</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>J. Kennedy and R. Eberhart. Particle swarm optimization. In ''Proceedings of IEEE International Conference on Neural Networks'', pages 1942-1948, IEEE Press, Piscataway, NJ, 1995.</div></td>
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Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4930&oldid=prev
Mmontes: /* History */
2008-11-07T15:07:00Z
<p><span dir="auto"><span class="autocomment">History</span></span></p>
<table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 15:07, 7 November 2008</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>their movement is governed by a set of rules. Some years later, Reynolds (1987) used a particle system to simulate the collective behavior of a flock of birds. In a similar kind of simulation, Heppner and Grenander (1990) included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>their movement is governed by a set of rules. Some years later, Reynolds (1987) used a particle system to simulate the collective behavior of a flock of birds. In a similar kind of simulation, Heppner and Grenander (1990) included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research, in particular <del class="diffchange diffchange-inline">Latané's</del> social impact<del class="diffchange diffchange-inline"> theory</del> (Nowak, Szamrej & Latané, 1990; Kennedy, 2006), was another source of inspiration in the development of the first particle swarm optimization algorithm. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).</div></td>
<td class="diff-marker">+</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research, in particular <ins class="diffchange diffchange-inline">the dynamic theory of</ins> social impact (Nowak, Szamrej & Latané, 1990; Kennedy, 2006), was another source of inspiration in the development of the first particle swarm optimization algorithm. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).</div></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
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Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4929&oldid=prev
Mmontes: /* History */
2008-11-07T15:02:08Z
<p><span dir="auto"><span class="autocomment">History</span></span></p>
<table class="diff diff-contentalign-left diff-editfont-monospace" data-mw="interface">
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Particle swarm optimization was introduced by Kennedy and Eberhart (1995). It has roots in the simulation of social behaviors using tools and ideas taken from computer graphics and social psychology research. </div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Particle swarm optimization was introduced by Kennedy and Eberhart (1995). It has roots in the simulation of social behaviors using tools and ideas taken from computer graphics and social psychology research. </div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Within the field of computer graphics, the first antecedents of particle swarm</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Within the field of computer graphics, the first antecedents of particle swarm<ins class="diffchange diffchange-inline"> optimization can be traced back to the work of Reeves (1983), who proposed particle systems to model objects that are dynamic and cannot be easily represented by polygons or surfaces. Examples of such objects are fire, smoke, water and clouds. In these models, particles are independent of each other and</ins></div></td>
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<td class="diff-marker"><a class="mw-diff-movedpara-right" title="Paragraph was moved. Click to jump to old location." href="#movedpara_4_6_lhs">⚫</a></td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><a name="movedpara_2_0_rhs"></a><ins class="diffchange diffchange-inline">their movement is governed by a set of rules. Some years later, Reynolds (1987) used a particle system to simulate the collective behavior of a flock of birds. In a similar kind of simulation, Heppner and Grenander (1990) </ins>included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>optimization can be traced back to the work of Reeves (1983), who proposed</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>particle systems to model objects that are dynamic and cannot be easily</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>represented by polygons or surfaces. Examples of such objects are fire, smoke,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>water and clouds. In these models, particles are independent of each other and</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>their movement is governed by a set of rules. Some years later, Reynolds</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>(1987) used a particle system to simulate the collective behavior of a flock</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>of birds. In a similar kind of simulation, Heppner and Grenander (1990)</div></td>
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<td class="diff-marker"><a class="mw-diff-movedpara-left" title="Paragraph was moved. Click to jump to new location." href="#movedpara_2_0_rhs">⚫</a></td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><a name="movedpara_4_6_lhs"></a>included a ''roost'' that was attractive to the simulated birds. Both models inspired the set of rules that were later used in the original particle swarm optimization algorithm.</div></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research was another source of inspiration in the development of the first particle swarm optimization algorithm. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).<del class="diffchange diffchange-inline"> </del></div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Social psychology research<ins class="diffchange diffchange-inline">, in particular Latané's social impact theory (Nowak, Szamrej & Latané, 1990; Kennedy, 2006),</ins> was another source of inspiration in the development of the first particle swarm optimization algorithm. The rules that govern the movement of the particles in a problem's solution space can also be seen as a model of human social behavior in which individuals adjust their beliefs and attitudes to conform with those of their peers (Kennedy & Eberhart 1995).</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"></td>
<td colspan="2" class="diff-empty"> </td>
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<td class="diff-marker">−</td>
<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><!--The name ''particle swarm'' was chosen because the collective behavior of the particles adheres to the principles described by Millonas (1994).--></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Standard PSO algorithm ==</div></td>
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Mmontes
https://iridia.ulb.ac.be/w/index.php?title=Particle_Swarm_Optimization_-_Scholarpedia_Draft&diff=4928&oldid=prev
Mmontes: /* Bare-bones PSO */
2008-11-07T14:23:00Z
<p><span dir="auto"><span class="autocomment">Bare-bones PSO</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Older revision</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 14:23, 7 November 2008</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In the bare-bones particle swarm optimization algorithm, a particle's position update rule in the <math>j</math>th dimension is</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In the bare-bones particle swarm optimization algorithm, a particle's position update rule in the <math>j</math>th dimension is</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math></div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>x^{t+1}_{ij} = N\left(\<del class="diffchange diffchange-inline">mu</del>^{t} ,\<del class="diffchange diffchange-inline">sigma</del>^{\,t}\right)\,,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>x^{t+1}_{ij} = N\left(\<ins class="diffchange diffchange-inline">mu_{ij}</ins>^{t} ,\<ins class="diffchange diffchange-inline">sigma_{ij}</ins>^{\,t}\right)\,,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>where <math>N</math> is a normal distribution with</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>where <math>N</math> is a normal distribution with</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div><math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\begin{array}{ccc}</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\begin{array}{ccc}</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>\<del class="diffchange diffchange-inline">mu</del>^{t} &=& \frac{b^{t}_{ij} + l^{t}_{ij}}{2} \,, \\</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>\<ins class="diffchange diffchange-inline">mu_{ij}</ins>^{t} &=& \frac{b^{t}_{ij} + l^{t}_{ij}}{2} \,, \\</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>\<del class="diffchange diffchange-inline">sigma</del>^{t} & = & |b^{t}_{ij} - l^{t}_{ij}| \,.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>\<ins class="diffchange diffchange-inline">sigma_{ij}</ins>^{t} & = & |b^{t}_{ij} - l^{t}_{ij}| \,.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\end{array}</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>\end{array}</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></math></div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div></math></div></td>
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Mmontes