Truss optimization with discrete design variables: a critical review

An evolutionary-based optimization algorithm for truss sizing design

“…The design variables are the bar element cross-section areas. The cross-section areas (in 2 is not necessary. To adapt the algorithm for problems with discrete variables, the rounding technique can be applied, i.e.…”

“…The design variables are the bar element cross-section areas. The cross-section areas (in 2 3 . The allowable stress is 25 ksi for both tension and compression stress in each member.…”

“…Metaheuristics such as genetic algorithms, particle swarm algorithms and evolution algorithms have been increasingly proposed as alternative techniques for optimization of truss structures [2]. Recently developed metaheuristics have shown good performance, for example, are: harmony search algorithm (SAHS) [3], teaching-learning-based optimization (TLBO) algorithm [4,5], chaotic swarming of particle (CSP) algorithm [6], colliding bodies optimization (CBO) [7,8], flower pollination algorithm (FPA) [9], water c 2016 Vietnam Academy of Science and Technology cycle algorithm (WCA) [10] and mine blast algorithm (MBA) [10,11], adaptive dimensional search (ADS) [12], and some new variants of the well-known differential evolution including adaptive differential evolution algorithm (ADEA) [1], improved constrained differential evolution using discrete variables (D-ICDE) [13], adaptive elitist differential evolution (aeDE) [14] and reliability-based improved constrained differential evolution (SORA-ICDE) [15].…”

A Quantitative Comparison Between Size, Shape, Topology and Simultaneous Optimization for Truss Structures

“…Given the complexity of the problem, the aid of a computerized metaheuristic search strategy such as genetic algorithms (GAs), evolution strategy (ES) or particle swarm optimization (PSO) is normally used for solving such problems. However, several works have used different methods to solve structural optimization problems (Pedersen, 1972;Zowe, 1994;Nielsen, 2003;Stolpe, 2016). Typically, the objective of the problem is to minimize the weight of the structure while still satisfying all the constraints.…”

Kaksivaiheinen menettely epälineaarisen diskreetin teräsrakenteiden optimointitehtävän ratkaisemiseksi

“…Menetelmiä on paljon ja esitetyt väitteet keskinäisestä paremmuudesta vaikuttaisivat olevan tehtävätyypistä riippuvaisia ja jossain määrin ristiriitaisia [1,5,6]. Myös kritiikkiä menetelmien hyvyydestä ja sen arvioinnista on esitetty [7]. Käytännön tehtävässä -vaikkapa suhteellisen rajatun tehtävän kuten ristikon -optimoinnissa vaadittava laskenta-aika monine ajoineen kasvaa helposti tunteihin [8].…”