A New Genetic Algorithm Methodology for Design Optimization of Truss Structures: Bipopulation-Based Genetic Algorithm with Enhanced Interval Search

Abstract

A new genetic algorithm (GA) methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS), is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA) utilizing a single population, a multipopulation-based genetic algorithm (MPGA) proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature.

Optimización de armaduras espaciales de acero utilizando algoritmos genéticos auto-adaptados: una primera aproximación

“…One comparison of quantity of structural analysis made indicates that there is no defined pattern to the behavior of the different methodologies. If the quantity of analysis made for GA from reference (4) and MCGA are compared, it is observed that the MCGA executed 6100 additional analysis for example 2 and 5200 less analysis for example 1.…”

“…The solution to the optimization problem requires the selection of a numerical technique capable of solving the current problem, in this case being the metaheuristics a group of optimization algorithms that has good performance (3)(4)(5)(6)(7). The metaheuristic is an approximate optimization algorithm used in the efficient determination of "adequate" solutions of difficult and complex problems in science and engineering, but it cannot guaranty an optimal solution (8) .…”

“…One of them consist in the definition of group of elements assigned with the same cross-section (3) to reduce the variable of the problem (therefor, reducing the search space of the solution). Considering the computational cost, the usage of solution representation schemes different from that of the binary codification could reduce significantly the time needed for the optimization of structure with great numbers of variables (4) . Additionally, improvements in the convergence process can be achieved by changing the way on how the violation of constrains is handled (5) , the usage of initial populations generated heuristically (6) and the modification of the genetic operators (like in the case of the usage of a probabilistic operator for the selection (7) ), among other strategies.…”

Probabilistic Adaptive Crossover Applied to Chilean Wine Classification

“…Once the estimation of the distribution is obtained, two parents are selected to generate new individuals, transferring the allele of each locus to the offspring in those places where the parents are equal and applying the estimated distribution to determine the alleles in those places where the parents have different values. Other similar techniques have been proposed by Varnamkhasti et al [45] and the one reported by Talaslioglu [46]. In the former, a new crossover operator and probability selection technique are proposed based on the population diversity using a fuzzy logic controller, whereas in the latter a bipopulation-based genetic algorithm with enhanced interval search is introduced.…”

A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis

“…The engineering problems related to structural design comprehend a wide number of situations: trussed systems optimization in both two-dimensional and three-dimensional (Coello and Cristiansen, 2000;Huang and Wang, 2008;Mroginski et al, 2009;Talaslioglu, 2009;Thein and Liu, 2012;Torii et al, 2012), topology analysis of plane frames structures (Stromberg et al, 2012), design of composite structural sections (Lopez et al, 2009), micromechanics optimization (Huang et al, 2011), performance of thermodynamic machines (Ahmadi et al, 2016;Sadatsakkak et al, 2015), fiber reinforced polymeric (Cai and Aref, 2015), among others.…”