The k-truss is a type of cohesive subgraphs proposed recently for the study of networks. While the problem of computing most cohesive subgraphs is NP-hard, there exists a polynomial time algorithm for computing k-truss. Compared with k-core which is also efficient to compute, k-truss represents the “core” of a k-core that keeps the key information of, while filtering out less important informat...

Abstract This paper includes three sections. Truss structures have been widely applied in bridges and buildings due to their light weight, reasonable load-bearing, high material utilization rate. For truss serving as load-bearing carriers, structural strength should be guaranteed, moreover, economic performance considered. First, the finite element theory was introduced, computer-aided simulati...

Abstract Despite the long history of truss layout optimization approach, its practical applications have been limited, partly due to high manufacturing costs associated with complex optimized structures consisting members different cross-sectional areas and member lengths. To address this issue, study considers optimizing comprising limited types members. On topic, two distinct problems are con...

fragility curves represent the probabilities that structural damages, under various levels of seismic excitation, will exceed the specified damage states by means of earthquake intensity damage relations. conceptual aspects related to seismic vulnerability, damage and risk evaluation are discussed first, together with a short review of the most widely used possibilities for the seismic evaluati...

Bat-inspired (BI) search is a recently developed numerical optimization technique that makes use of echolocation behavior of bats in seeking a design space. This study intends to explore capabilities and potentials of this newly developed method in the realm of structural optimization. A novel algorithm is developed that employs basic principles of this method for structural optimization proble...

Structural optimization with frequency constraints is a challenging class of optimization problems characterized by highly non-linear and non-convex search spaces. When using a meta-heuristic algorithm to solve a problem of this kind, exploration/exploitation balance is a key feature to control the performance of the algorithm. An excessively exploitative algorithm might focus on certain areas ...