Multi-objective optimal structural design of composite superstructure using a novel MONMPSO algorithm

•A novel Multi-Objective Niching Memetic Particle Swarm Optimization (MONMPSO) algorithm is proposed for solving constrained multi-objective optimization problems.•Multi-objective optimal structural design of composite sandwich panel is done by considering:üObjective functions: the weight and the co...

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Bibliographic Details
Published in:International journal of mechanical sciences Vol. 193; p. 106149
Main Authors: Gholami, Meghdad, Fathi, Alireza, Baghestani, Ali Mohammad
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.03.2021
Subjects:
Composite sandwich panel
Constrained multi-objective optimization
Fiber-reinforced laminate
FSDT
MONMPSO
NSGA-II
Constrained multi-objective optimization
NSGA-II
Composite sandwich panel
Fiber-reinforced laminate
FSDT
MONMPSO
ISSN:0020-7403, 1879-2162
Online Access:Get full text
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Summary:•A novel Multi-Objective Niching Memetic Particle Swarm Optimization (MONMPSO) algorithm is proposed for solving constrained multi-objective optimization problems.•Multi-objective optimal structural design of composite sandwich panel is done by considering:üObjective functions: the weight and the cost.üOptimization parameters: the materials of fiber, matrix and core, the laminate arrangements and construction, the amount of fiber reinforcement, the thickness of the core and the thicknesses of the lamina, laminate and panel.üLoads: out of plane pressure and buckling load.üThe base theory : first-order shear deformation laminated plate theory (FSDT).•Pareto front-optimal solutions are obtained for various problem cases. As an application of composite science in the marine industry, the present paper deals with the multi-objective optimal structural design of a superstructure composite sandwich panel based on the first-order shear deformation laminated plate theory (FSDT). Several parameters including the type of fiber, matrix and core material, the amount of reinforcement, the core, lamina and laminate thickness, the laminate arrangement (stacking sequence) and the laminate construction are considered as the design parameters. A novel Multi-Objective Niching Memetic Particle Swarm Optimization (MONMPSO) algorithm is proposed and its performance is evaluated using the well-known non-dominated sorting genetic algorithm (NSGA-II). The results show that the proposed MONMPSO algorithm has a better performance in comparison to the NSGA-II algorithm in extracting the Pareto front pattern. Based on the numerical results, many useful structural rules for designing a composite sandwich panel under the out of plane pressure and buckling load have been deduced. [Display omitted]
ISSN:0020-7403
1879-2162
DOI:10.1016/j.ijmecsci.2020.106149