This paper presents an optimization algorithm based on Simulated Annealing. The algorithm - denoted as CMLPSA (Corrected Multi Level & Multi Point Simulated Annealing) - implements an advanced search mechanism where each candidate design is selected from a population of trial points randomly generated. Therefore, CMLPSA is in principle similar to meta-heuristic algorithms dealing with a population of candidate designs rather than with a single trial point such as it is usually done in classical simulated annealing. Perturbations given to optimization variables are forced to follow the current rate of change exhibited by the cost function. CMLPSA is tested in 9 optimization problems where the objective is to minimize the weight of bar truss structures - with up to 200 elements - subjected to constraints on nodal displacements, member stresses and critical buckling loads. Test cases include both sizing and configuration variables. The computationally most expensive problem has 200 design variables and 3500 optimization constraints. Results demonstrate that CMLPSA is very competitive with respect to other advanced global optimization methods like Harmony Search (HS) and Heuristic Particle Swarm Optimization (HPSO) recently presented in literature.
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|Titolo:||Confronto di algoritmi meta-euristici per l’ottimizzazione di strutture reticolari|
|Data di pubblicazione:||2007|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|