Effect of algorithm techniques on optimization of laminate stacking sequence for buckling load condition - Pitchumani, Shenbaga Velu; Gopu, Arunkumar; Gopalan, Venkatachalam; Narayanan, V. Neela; Guru, A. (International journal on interactive design and manufacturing, 2025)
In the present work, the temperature of deformation of a composite reinforced with natural fibres (NFRC) material is investigated and then optimized using four different techniques such as BAT algorithm, particle swarm optimization (PSO), Genetic algorithm (GA) and differential evolution (DE). Boundary conditions (BC), aspect ratio (AR) and ply orientation (PO) are the three input parameters used to evaluate the thermal buckling temperature of the jute fibre-reinforced polymer matrix composite. In this study, to achieve a maximum thermal buckling temperature of the NFRC, the authors focus on the influence of the input parameters. The results reveal that boundary conditions, aspect ratio and ply orientation are found to be important influencing factors on the buckling temperature. The output relationships of the variables are examined with finite element analysis, and the BAT, DE, and PSO/GA curves are used to determine the best process parameters. DE generates the population-based metaheuristic model for NFRC reinforced with jute fibres. Results from both the PSO and BAT models are in good agreement with those from experiments. The stronger correlation of GA values than DE values during testing, training, and validation leads researchers to conclude that BAT models are more accurate than PSO. The aspect ratio seems less significant, according to the numerical data, while ply orientation and boundary condition content are significant factors that increase buckling strength.