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
Metamodel-based optimization of a control arm considering strength and durability performance
Computers & Mathematics with Applications
Optimization Methods & Software - The International Conference on Engineering Optimization (EngOpt 2008)
Structural optimization based on CAD-CAE integration and metamodeling techniques
Computer-Aided Design
Truss optimization with dynamic constraints using a particle swarm algorithm
Expert Systems with Applications: An International Journal
Structural and Multidisciplinary Optimization
Hybrid population-based incremental learning using real codes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
IEEE Transactions on Evolutionary Computation
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This paper proposes hybridisation of evolutionary algorithms (EAs) and an efficient search strategy for truss optimisation. During an optimisation process, function gradients are approximated using already explored design solutions. The approximate gradient is then employed as a local search direction. The approximate gradient operator is integrated into the main search procedure of three multiobjective evolutionary algorithms (MOEAs) leading to three hybrid optimisers. The proposed hybrid strategies along with their original MOEAs are implemented on multiobjective design of truss structures. From the comparative results, it is found that the approximate gradient operator can greatly improve the search performance of MOEAs.