A hybrid algorithm coupling genetic programming and Nelder–Mead for topology and size optimization of trusses with static and dynamic constraints

Assimi, Hirad; Jamali, Ali

doi:10.1016/j.eswa.2017.11.035

Cited by 44 publications

(12 citation statements)

References 40 publications

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“…Recent single objective structural optimization studies (power transmission towers) report material savings ranging from 6% to 12% [6,9,10] less than the initial design. Many structural optimization problems of trusses have been solved based on a single objective function, usually structural weight [11,12]. However, in practical situations, the designer must identify several objective functions (the most convenient) to measure economy, strength, serviceability and other factors affecting the structure's performance [1].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective topology optimization of planar trusses using stress trajectories and metaheuristic algorithms

Niño-Alvarez

Begambre-Carrillo

2022

Rev.Fac.Ing.Univ.Antioquia

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In civil engineering, structural optimization seeks an efficient use of material resources and the automatization of the design process of a wide range of structures such as frames, bridges, and other systems. This work develops a novel multiobjective topology optimization process to minimize planar trusses' weight and strain energy. In the initial stage, an optimized discrete geometry of the ground structure is generated from a continuum design space with general boundary conditions (loads and supports) using the stress trajectories theory. In the final stage, size optimization is performed using the concept of Envelope Pareto Front (EVP), which is obtained from the best solutions provided by three efficient multiobjective metaheuristic algorithms (NSGA-II, MOPSO and AMOSA). The results obtained on a large-scale truss (200 m span continuous bridge) showed that innovative geometries could be found (new connectivity patterns). The generation of an EVP allows getting a more significant number of non-dominated solutions, exploring a broader region of the Pareto front and the two objective functions, achieving greater convergence and diversity than the algorithms' individual performance. The computation cost of the optimization strategy was satisfactory, which allows its potential implementation in actual large-scale trusses, discovering optimized, innovative solutions for this type of structures.

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Section: Introductionmentioning

confidence: 99%

Multiobjective topology optimization of planar trusses using stress trajectories and metaheuristic algorithms

Niño-Alvarez

Begambre-Carrillo

2022

Rev.Fac.Ing.Univ.Antioquia

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“…Assimi and Jamali [34] describe a hybrid algorithm coupling genetic programming and Nelder-Mead for topology and size optimization of trusses with static and dynamic constraints.…”

Section: Introductionmentioning

confidence: 99%

Sizing and Topology Optimization of Trusses Using Genetic Algorithm

et al. 2021

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Genetic algorithms are a robust method for a solution of wide variety optimization problems. It explores a big space of design variables in order to find the best solution. From the point of view of a user, the algorithm requires the encoding of design variables into the form of strings and the procedure of optimization uses them for optimization. Here, for the structural engineer, it is crucial to find the form of objective function including the constraints of the task and also to avoid critical states during the solution of structural responses. This paper presents the use of genetic algorithm for solving truss structures. The use of genetic algorithm approach is shown on three cases of truss structures.

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“…Researchers in [4,5] showed the need for using discrete cross-section variable sets in order to match available, standard, dimensions of cross-section profiles. The implementation of Euler buckling constraints has increasingly started becoming part of the mathematical model in most research [6][7][8]. Optimization of trusses without buckling constraints gives low masses like in [9][10][11][12], but unstable constructions.…”

Section: Introductionmentioning

confidence: 99%

Sizing and shape optimization material use in 10 bar trusses

et al. 2021

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Truss optimization has the goal of achieving savings in costs and material while maintaining structural characteristics. In this research a 10 bar truss was structurally optimized in Rhino 6 using genetic algorithm optimization method. Results from previous research where sizing optimization was limited to using only three different cross-sections were compared to a sizing and shape optimization model which uses only those three cross-sections. Significant savings in mass have been found when using this approach. An analysis was conducted of the necessary bill of materials for these solutions. This research indicates practical effects which optimization can achieve in truss design.

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A hybrid algorithm coupling genetic programming and Nelder–Mead for topology and size optimization of trusses with static and dynamic constraints

Cited by 44 publications

References 40 publications

Multiobjective topology optimization of planar trusses using stress trajectories and metaheuristic algorithms

Multiobjective topology optimization of planar trusses using stress trajectories and metaheuristic algorithms

Sizing and Topology Optimization of Trusses Using Genetic Algorithm

Sizing and shape optimization material use in 10 bar trusses

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