... and parametric diversity on the effectiveness of design-space exploration. Generative design Genetic algorithms Computational design synthesis Powertrain design Automatic control tuning Business Finland Dnr 31/31/2024 http://dx.doi.org/10.13039/501100014438 Funding: This work...

... of transpiration index with respect to five inputs Optimization Quantification Genetic algorithms Parametric analysis Therefore, this work shall introduce an application of GP to develop the function relationship of the transpiration index with respect to five inputs (root area, root biomass, stem...

... to assess the concentration of copper into the oils and, thus, evaluate the wearing of the machinery. It was found that the use of SVR was very advantageous to get a regression model. Originality/value – The use of genetic algorithms coupled to SVR was considered in order to reduce the time needed...

...Afonso C.C Lemonge; Helio J.C. Barbosa; Heder S. Bernardino Purpose – The purpose of this paper is to propose variants of an adaptive penalty scheme for steady-state genetic algorithms applied to constrained engineering optimization problems. Design/methodology/approach – For each...

... risk and variation in returns. Moreover, the authors employ the genetic algorithm for optimization of model parameters and selection for input variables simultaneously. Findings – It is found that the proposed risk-adjusted methodology via maximum drawdown significantly outperforms the benchmark...

... intelligence techniques and methodologies like Fuzzy Logic, neural networks and/or genetic algorithms (GA). Artificial intelligence techniques complement classical methodologies and include concepts that simulate the way humans solve problems or how processes work in nature. In this work, the Fuzzy Logic...

... that the paper resolves using genetic algorithms (GAs). Design/methodology/approach – The lite PRNs are obtained by using NSGA-II and omni-optimizer multi-objective optimization techniques. Findings – The new PRNs obtained with the proposed single/multi-objective solutions are always better than...

...M. Vaz Jr; E.L. Cardoso; J. Stahlschmidt Purpose – Parameter identification is a technique which aims at determining material or other process parameters based on a combination of experimental and numerical techniques. In recent years, heuristic approaches, such as genetic algorithms (GAs), have...

... in complex design domains without additional tuning when changing the design domain. These go from an academic design domain to a practical one. Design/methodology/approach Various crossovers operators are applied over the same representation using a genetic algorithm for truss structural optimization...

... of this approach is to identify and preserve the common schema of the two parents responsible for their high‐observed fitness. The proposed hybrid crossover operator is embedded into a genetic algorithm supported by an elitist strategy and its performance is compared with the parametrised uniform crossover...

...Liu Xiyu; Tang Mingxi; John Hamilton Frazer This paper presents a new surface reconstruction method based on complex form functions, genetic algorithms and neural networks. Surfaces can be reconstructed in an analytical representation format. This representation is optimal in the sense of least...

... less vibration/noise compared to the original design. The optimization method used, was based on genetic algorithms (GAs). GAs are a robust optimization method that performs regardless of the optimization problem. The GA‐based optimization method that is presented in this paper, utilized ANSYS running...

...Kwong‐Sak Leung; Jian‐Yong Sun; Zong‐Ben Xu In this paper, a set of safe adaptive genetic algorithms (sGAs) is proposed based on the Splicing/Decomposable encoding scheme and the efficient speed‐up strategies developed by Xu et al.. The proposed algorithms implement the self‐adaptation...

... design) and the genetic algorithm GA (a stochastic search method, inspired by the natural evolution model) are compared. The minimum weight design of truss structures subjected to stress and displacement constraints is investigated, including the case of multiple load conditions. The discrete design...

...V.V. Toropov; S.Y. Mahfouz In this paper a structural optimization technique based on a modified genetic algorithm (GA) is presented. The technique is developed to deal with discrete design optimization of structural steelwork. Also, the paper discusses the effect of different approaches, employed...

...Hui‐Yuan Fan; Jane Wei‐Zhen Lu; Zong‐Ben Xu Genetic algorithms have been extensively used in different domains as a type of robust optimization method. They have a much better chance of achieving global optima than conventional gradient‐based methods which usually converge to local sub‐optima...

... and the actuator configurations cannot be optimized independently, since the effect of the ANC system is directly involved in the combined sensor and actuator configuration. For the solution of this problem several intelligent techniques were applied. In this paper the successful application of a genetic algorithm...

...M.R. Ghasemi; E. Hinton; R.D. Wood This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar...

...M.F. Yeo; E.O. Agyei This paper deals with the optimisation of engineering problems using genetic algorithms. The process is discussed and the various stages of the genetic algorithm described. In conjunction with a finite element analysis program the process is then applied to a realistic problem...

...R.L. WOOD In principle, it is possible to apply genetic algorithms (GAs) to the solution of inverse problems in the simulation of manufacturing processes. In this context, an inverse problem can be stated as ‘knowing the desired output of a process, what combination of process parameters...