000013292 001__ 13292
000013292 005__ 20161114160335.0
000013292 04107 $$aeng
000013292 046__ $$k2009-06-22
000013292 100__ $$aDimou, C.
000013292 24500 $$aInvestigation of the robustness of pso algorithms in reliability optimal design problems

000013292 24630 $$n2.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000013292 260__ $$bNational Technical University of Athens, 2009
000013292 506__ $$arestricted
000013292 520__ $$2eng$$aIn this work, the robustness of two variants of the Binary Particle Swarm Optimization algorithm (ΒPSO) are examined, in the Reliability Based Optimal Design (RBOD) of determinate truss structures. Particle swarm optimization (PSO) [1] is a population based stochastic optimization method inspired from the social behavior of birds or insects. In the first variant, the Binary Repulsive PSO (BRPSO), the velocity vector uses information obtained from an optimal solution found by the neighbors of the individual, the individual’s memory, its current velocity vector and some “noise”. Repulsive PSO is considered robust in very complex search space with numerous local optima [2]. The second variant is the Binary PSO incorporating the “craziness” operator. When craziness is implemented a subset of the particles is selected, and their position and/or velocity vectors are re-initialized [3]. The robustness of these variants is examined in the RBOD of a 25-bar truss and a 30-bar arch. The results of the investigated optimization schemes, for these two problems, are compared with the results obtained from the BPSO and the Standard Genetic Algorithm (SGA) and the relative performance of all variants is discussed.

000013292 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000013292 653__ $$aParticle Swarm Optimization, Reliability Based Optimal Design, truss structures, Repulsive PSO, craziness operator. Abstract. In this work, the robustness of two variants of the Binary Particle Swarm Optimization algorithm (ΒPSO) are examined, in the Reliability Based Optimal Design (RBOD) of determinate truss structures. Particle swarm optimization (PSO) [1] is a population based stochastic optimization method inspired from the social behavior of birds or insects. In the first variant, the Binary Repulsive PSO (BRPSO), the velocity vector uses information obtained from an optimal solution found by the neighbors of the individual, the individual’s memory, its current velocity vector and some “noise”. Repulsive PSO is considered robust in very complex search space with numerous local optima [2]. The second variant is the Binary PSO incorporating the “craziness” operator. When craziness is implemented a subset of the particles is selected, and their position and/or velocity vectors are re-initialized [3]. The robustness of these variants is examined in the RBOD of a 25-bar truss and a 30-bar arch. The results of the investigated optimization schemes, for these two problems, are compared with the results obtained from the BPSO and the Standard Genetic Algorithm (SGA) and the relative performance of all variants is discussed.

000013292 7112_ $$aCOMPDYN 2009 - 2nd International Thematic Conference$$cIsland of Rhodes (GR)$$d2009-06-22 / 2009-06-24$$gCOMPDYN2009
000013292 720__ $$aDimou, C.$$iKoumousis V., K.
000013292 8560_ $$ffischerc@itam.cas.cz
000013292 8564_ $$s271693$$uhttps://invenio.itam.cas.cz/record/13292/files/CD434.pdf$$yOriginal version of the author's contribution as presented on CD, section: Structural optimization.
000013292 962__ $$r13074
000013292 980__ $$aPAPER