Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Parallel simulated annealing algorithms
Journal of Parallel and Distributed Computing
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
A novel optimization approach for minimum cost design of trusses
Computers and Structures
An efficient simulated annealing algorithm for design optimization of truss structures
Computers and Structures
Size optimization of space trusses using Big Bang-Big Crunch algorithm
Computers and Structures
Geometry and topology optimization of geodesic domes using charged system search
Structural and Multidisciplinary Optimization
Optimal design of truss-structures using particle swarm optimization
Computers and Structures
MGA – a mathematical approach to generate design alternatives
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Multimodal size, shape, and topology optimisation of truss structures using the Firefly algorithm
Advances in Engineering Software
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
Fully Stressed Design Evolution Strategy for Shape and Size Optimization of Truss Structures
Computers and Structures
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This paper addresses to the development of a simulated annealing (SA) based solution algorithm for the simultaneous optimum design of truss type structures with respect to size, shape and topology design variables. The proposed algorithm is designed in such way that together with applicability to practical design problems, it also aims to produce efficient and improved design solutions for the problems of interest. From the practical point of view, the objective chosen is to minimise the weight of the structures under a set of particular constraints imposed by design code specifications on nodal displacement, member stress and stability. Concerning the efficiency of the algorithm, SA is adapted to be able to work fruitfully in the design spaces of complex problems occupied by many regions of highly different characteristics. The proposed algorithm is tested on two large design example problems taken from the literature for comparison purposes and the results are fully discussed.