Optimum design of steel structures with the particle swarm optimization method based on EC3

Plevris, V; Batavanis, A; Papadrakakis, M

dc.contributor.author	Plevris, V	en
dc.contributor.author	Batavanis, A	en
dc.contributor.author	Papadrakakis, M	en
dc.date.accessioned	2014-03-01T02:53:25Z
dc.date.available	2014-03-01T02:53:25Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36301
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-80054825054&partnerID=40&md5=37e21be27266eb6dd302c2246ad2e623	en
dc.subject	EC3	en
dc.subject	Optimum design	en
dc.subject	Particle swarm optimization	en
dc.subject	Steel structures	en
dc.subject.other	Analysis results	en
dc.subject.other	Applied loads	en
dc.subject.other	Axial forces	en
dc.subject.other	Biaxial bending	en
dc.subject.other	Constraint reactions	en
dc.subject.other	Design spaces	en
dc.subject.other	EC3	en
dc.subject.other	Eurocode 3	en
dc.subject.other	Evolution strategies	en
dc.subject.other	Fine tuning	en
dc.subject.other	Finite element software	en
dc.subject.other	Gradient based	en
dc.subject.other	Linear analysis	en
dc.subject.other	Mathematical algorithms	en
dc.subject.other	Natural phenomena	en
dc.subject.other	Nodal displacement	en
dc.subject.other	Nonconvex optimization	en
dc.subject.other	Optimization algorithms	en
dc.subject.other	Optimization method	en
dc.subject.other	Optimum designs	en
dc.subject.other	Particle swarm	en
dc.subject.other	Particle swarm optimization method	en
dc.subject.other	Physical movements	en
dc.subject.other	Potential solutions	en
dc.subject.other	PSO algorithms	en
dc.subject.other	Search Algorithms	en
dc.subject.other	Setting parameters	en
dc.subject.other	Shear force	en
dc.subject.other	Social interactions	en
dc.subject.other	Software tool	en
dc.subject.other	Speed of convergence	en
dc.subject.other	Steel frame	en
dc.subject.other	Structural design optimization	en
dc.subject.other	Test examples	en
dc.subject.other	Velocity vectors	en
dc.subject.other	Biology	en
dc.subject.other	Civil engineering	en
dc.subject.other	Computational methods	en
dc.subject.other	Computer programming	en
dc.subject.other	Computer software	en
dc.subject.other	Constrained optimization	en
dc.subject.other	Convex optimization	en
dc.subject.other	Cooling systems	en
dc.subject.other	Design	en
dc.subject.other	Earthquakes	en
dc.subject.other	Engineering geology	en
dc.subject.other	Finite element method	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Shape optimization	en
dc.subject.other	Steel structures	en
dc.subject.other	Structural analysis	en
dc.subject.other	Structural dynamics	en
dc.subject.other	Structural optimization	en
dc.subject.other	Three dimensional	en
dc.subject.other	Vector spaces	en
dc.subject.other	Particle swarm optimization (PSO)	en
dc.title	Optimum design of steel structures with the particle swarm optimization method based on EC3	en
heal.type	conferenceItem	en
heal.publicationDate	2011	en
heal.abstract	A number of optimization algorithms have been used in structural design optimization in the past, ranging from gradient-based mathematical algorithms to probabilistic-based search algorithms, for addressing global non-convex optimization problems. Many probabilistic-based algorithms have been inspired by natural phenomena, such as Evolutionary Programming (EP), Genetic Algorithms (GA), Evolution Strategies (ES), among others. Recently, a family of optimization methods has been developed based on the simulation of social interactions among members of a specific species. One of these methods is the Particle Swarm Optimization (PSO) method that is based on the behavior reflected in flocks of birds, bees and fish that adjust their physical movements to avoid predators and seek for food. In PSO, as in GA, a population of potential solutions is considered and utilized to search within the design space. However, its members do not reproduce but rather communicate with each other their knowledge of solutions in order to reach the optimum. Each ""particle"", ""flies"" through the multi-dimensional design space, with a certain velocity vector for each iteration. In this study, a discrete PSO algorithm is employed for the optimization of 2D and 3D steel frames and the results are compared to the ones obtained with a discrete GA. Both methods are applied in single-objective, discrete, constrained structural engineering optimization problems where the aim is to minimize the weight of the steel structure under various constraints on displacements and forces (biaxial bending with axial force and shear force) which are based on Eurocode 3. The constraints are checked by performing a Finite Element analysis for every candidate optimum design. A new linear analysis software tool for three-dimensional frames has been developed, featuring some distinct characteristics. The applied loads can be nodal or elemental (uniform, triangular or trapezoidal in any direction within an element), while any release (translational or rotational) can be implemented at an end of any element, in any of the 6 Degrees Of Freedom (DOFs). The output of the analysis program includes the constraint reactions, nodal displacements, forces at the ends of the elements, plus the displacements of the released DOFs of all elements with releases, and any displacement or any force at any given point within an element. The accuracy of the analysis results is verified by a direct comparison to the corresponding results of a reliable commercial finite element software program. For each method, the performance, functionality and effect of different setting parameters are studied. After a fine tuning of the parameters, the results are compared to each other. The comparison is done with regard to the speed of convergence, in terms of number of objective function evaluations, and accuracy of the solution. Various 2D and 3D steel structures are considered as test examples.	en
heal.journalName	ECCOMAS Thematic Conference - COMPDYN 2011: 3rd International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering: An IACM Special Interest Conference, Programme	en