Many real-world engineering design problems are naturally cast in the form of optimization programs with uncertainty-contaminated data. In this context, a reliable design must be able to cope in some way with the presence of uncertainty. In this paper, we consider two standard philosophies for finding optimal solutions for uncertain convex optimization problems. In the first approach, classical...

Optimization of truss-structures for finding optimal cross-sectional size, topology, and configuration of 2-D and 3-D trusses to achieve minimum weight is carried out using real-coded genetic algorithms (GAs). All the above three optimization techniques have been made possible by using a novel representation scheme. Although the proposed GA uses a fixed-length vector of design variables represe...

The purpose of this paper is to verify the applicability of the prototype of the Neural Network base model for Optimum Structural Design(NNOSD) to search the optimum design in all cases immediately. NNOSD suggest the procedure of the optimum design and the proper values of the neural network variables(training pattern, number of hidden neurons, maximum training error, steepness coefficient, lea...

Optimization of truss-structures for finding optimal cross-sectional size, topology, and configuration of 2-D and 3-D trusses to achieve minimum weight is carried out using real-coded genetic algorithms (GAs). All the above three optimization techniques have been made possible by using a novel representation scheme. Although the proposed GA uses a fixed-length vector of design variables represe...

the present study tackled the modeling of dynamic truss structure using a topological approach. This approach is based on the notion of topological collections and transformations by applying the MGS language (Modeling of General System). For this purpose the MGS language was presented and applied in the case of N bar truss structure. Then, results obtained by MGS language were compared to thos...

Truss layout optimization under complex constraints has been a hot and challenging problem for decades that aims to find the optimal node locations, connection topology between nodes, cross-sectional areas of connecting bars. Monte Carlo Tree Search (MCTS) is reinforcement learning search technique competent solve decision-making problems. Inspired by success AlphaGo using MCTS, truss formulate...

Abstract Manipulating the architecture of materials to achieve optimal combinations properties (inverse design) has always been dream scientists and engineers. Lattices represent an efficient way obtain lightweight yet strong materials, providing a high degree tailorability. Despite massive research done on lattice architectures, inverse design problem complex phenomena (such as structural inst...