An improved genetic algorithm with initial population strategy and self-adaptive member grouping
Computers and Structures
A heuristic particle swarm optimization method for truss structures with discrete variables
Computers and Structures
Size optimization of space trusses using Big Bang-Big Crunch algorithm
Computers and Structures
A new optimization method: Big Bang-Big Crunch
Advances in Engineering Software
Optimum design of skeletal structures using imperialist competitive algorithm
Computers and Structures
An exponential big bang-big crunch algorithm for discrete design optimization of steel frames
Computers and Structures
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This study presents a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses. The method works on the basis of guiding the optimization process using the well-known principle of virtual work as well as the information collected during the structural analysis and design stages. The performance of the proposed technique is investigated through a benchmark truss instance as well as four real-size trusses sized for minimum weight according to AISC-LRFD specifications. A comparison of the numerical results obtained using the GSS with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser computational effort.