User:Siamaktalat/Charged System Search

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Charged System Search, a novel met-heuristic optimizer

Charged System Search (CSS) is a new optimization algorithm based on some principles from physics and mechanics. CSS utilizes the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a Charged Particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space.

References[edit]

[1] A. Kaveh and S. Talatahari, A Novel Heuristic Optimization Method: Charged System Search, Acta Mechanica, Volume 213, Issues 3-4 Pages 267-289 (2010).

[2] A. Kaveh and S. Talatahari, Optimal Design of Skeletal Structures via The Charged System Search Algorithm, Structural and Multidisciplinary Optimization, Volume 41, Issue 6, Pages 893-911 (2010).

[3] A. Kaveh and S. Talatahari, Charged System Search for Optimum Grillage Systems Design Using the LRFD-AISC Code, Journal of Constructional Steel Research, Volume 66, Issue 6, Pages 767-771 (2010).

[4] A. Kaveh and S. Talatahari, A Charged System Search with A Fly to Boundary Method for Discrete Optimum Design of Truss Structures, Asian Journal of Civil Engineering, Volume 11, Issue 3, Pages 277-293 (2010).

[5] A. Kaveh and S. Talatahari, Geometry and Topology Optimization of Geodesic Domes Using Charged System Search, Structural and Multidisciplinary Optimization, 2010, DOI: 10.1007/s00158-010-0566-y.

[6] A. Kaveh and S. Talatahari, An Enhanced ‎‎Charged System Search for Configuration ‎Optimization Using the Concept of Fields of Forces, Structural and Multidisciplinary Optimization, DOI: 10.1007/s00158-010-0571-1.

[7] A. Kaveh and S. Talatahari, Hybrid Charged System Search and Particle Swarm Optimization for Engineering Design Problems, Engineering Computations, International Journal for Computer-Aided Engineering and Software, accepted for publication, 2010.

External links[edit]

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