Abstract Structural topological optimization is the most general form of structural optimization and requires a less detailed description of the concept. One of the most exciting and challenging problems in this field is to find optimized layouts with minimization of compliance (maximization of stiffness) for a given total mass of the structure discretized by truss members, which cannot be well solved by evolutionary algorithms. Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence which is inspired by concepts from ‘Social Psychology’ and ‘Artificial Life’. PSO is particularly a preferable candidate to solve highly nonlinear, non-convex and even discontinuous problems and has been applied to many different kinds of optimization problems. The motivation of this paper is to propose an enhanced Lbest based PSO and geometrical consistency check tightly connecting to the ground structure approach to break through in this optimization field. Through a popular benchmark test, two kinds of Modified Lbest based PSO (MLPSO) exhibited competitive performance due to improved global searching ability.


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    Title :

    Solving truss topological optimization via Swarm Intelligence


    Contributors:
    Yang, Bin (author) / Zhang, Qilin (author) / Zhou, Zhihao (author)

    Published in:

    Publication date :

    2015-02-06


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Solving truss topological optimization via Swarm Intelligence

    Yang, Bin / Zhang, Qilin / Zhou, Zhihao | Online Contents | 2015




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