.... Design/methodology/approach The proposed framework integrates finite element analysis (FEA) with three optimization algorithms: derivative-free optimization (DFO) using the Nelder–Mead method, particle swarm optimization (PSO) and genetic algorithm (GA). A standardized problem setup is employed...

... influenced the work reported in this paper. 01 07 2025 09 09 2025 27 10 2025 © Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only CF-ABS ANN-PSO Genetic algorithm 3D printing Gibson et al. (2015) , Gao et al...

... a geostatistical approach based on adaptive kriging (AK) with a genetic algorithm (GA) based on Non-dominated Sorting Genetic Algorithm II (NSGA II) operating on a dedicated mesh. An initial set of random designs is selected by Latin hypercube sampling (LHS). The machine learning technique based on k-means groups...

...Primož Potočnik; Anish Nair; Andrej Jeromen; Edvard Govekar Purpose The purpose of this paper is to apply an innovative evolutionary approach based on a genetic algorithm (GA) for optimizing laser beam (LB) paths in laser-based additive manufacturing (LBAM) with the aim of minimizing deformation...

... in solving this NP-hard problem by a hybrid evolutionary heuristic. Design/methodology/approach First, a set of transition firing sequences (TFSs) consistent with the observed label sequences is found to generate the initial population of the genetic algorithm (GA). Second, we calculate the initial...

... by using a genetic algorithm method to get enhanced controller performance. The active control is implemented in an eight degrees of freedom (8-DOF) vehicle suspension model, subjected to a standard ISO road profile. The control performance is compared against a controlled system with few Q and R...

... response alleviation. To this end, this paper proposes a novel adaptive linear quadratic regulator (LQR) by integrating wavelet transform and genetic algorithm (GA). Design/methodology/approach In each time interval, multiresolution analysis of real-time structural responses returns filtered time...

.../approach In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance...

... precision is not high. Design/methodology/approach A new three-dimensional coordinate measurement algorithm by optimizing back propagation (BP) neural network based on genetic algorithm (GA) is proposed. The mapping relation between three-dimensional coordinates of space points in the world coordinate...

... to design an efficient assembly line while satisfying a set of constraints. Design/methodology/approach An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP to optimize the number of stations and the workload smoothness. Findings To evaluate the performance of the IGA...

...Soukaina Laabadi; Mohamed Naimi; Hassan El Amri; Boujemâa Achchab Purpose The purpose of this paper is to provide an improved genetic algorithm to solve 0/1 multidimensional knapsack problem (0/1 MKP), by proposing new selection and crossover operators that cooperate to explore the search space...

... of gravity; h denotes the height. Next, we have: © Emerald Publishing Limited 2019 Emerald Publishing Limited Licensed re-use rights only Genetic algorithm Benchmark Constrained optimization WA Many application problems can be transferred to optimization models...

...Elisabetta Sieni; Paolo Di Barba; Fabrizio Dughiero; Michele Forzan Purpose The purpose of this paper is to present a modified version of the non-dominated sorted genetic algorithm with an application in the design optimization of a power inductor for magneto-fluid hyperthermia (MFH). Design...

.... An optimization problem formulation is proposed and a Genetic Algorithm is used. Multi-objective optimization problems balancing failure strength and ductility criteria are solved providing optimal mixtures of fibres whose properties may come either from a pre-defined list of materials, currently available...

... for placing sensor and actuator in large-scale systems by using restricted genetic algorithm (RGA). RGA is a kind of genetic algorithm which is developed specifically for sensors and actuator placement. Findings Unlike its other counterparts, the proposed method not only supports unstable systems but also...

...Hamid Nayebpur; Mohsen Nazem Bokaei Purpose The purpose of this paper is to present a new technique to portfolio selection using a genetic algorithm (GA) and fuzzy synthetic evaluation (FSE). Portfolio selection is a multi-objective/criteria decision-making problem in financial management...

... Vehicle Simulation (DTVSim) is used to model the inflation and descent of the reefed parachute system. It is solved by the fourth-order Runge–Kutta method, and the opening load values are thereby obtained. A parallel genetic algorithm (GA) code is developed to optimize the reefed parachute. A penalty...

... parameters of the selected material model were performed. The optimisation process consists of the method for design of experiment, modelling a response surface and a genetic algorithm. Findings The paper provides comparison of two optimisation processes with different methods for design of experiment...

... genetic algorithm. Design/methodology/approach The proposed fully 3D computational fluid dynamics (CFD) model makes use of the Reynold stress model for the accurate prediction of turbulence, while the particle trajectories are simulated using the one-way coupling discrete phase, which is a model...

... approach to the automated element grouping and self-stress identification of tensegrities. Design/methodology/approach – A set of feasible solutions conforming to the unilateral behaviour of elements is obtained through an optimisation process, which is solved using a genetic algorithm. Each...