Structural topology optimization using ant colony optimization algorithm

Luh, Guan-Chun; Lin, Chun-Yi

doi:10.1016/j.asoc.2009.06.001

Cited by 79 publications

(29 citation statements)

References 35 publications

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“…198.064 (6) 252.258 (7) 285.161 (8) 363.225 (9) 388.386 (10) 494.193 (11) 506.451 (12) 641.289 (13) 645.160 (14) 729.031 (15) 792.256 (16) 816.773 (17) 939.998 (18) 1008.385 (19) 1045.159 (20) 1161.288 (21) 1283.868 (22) 1374.191 (23) 1535.481 (24) 1690.319 (25) 1696.771 (26) 1858.061 (27) 1890.319 (28) 1993.544 (29) 2180.641 (30) 2238.705 (31) 2290.318 (32) 2341.931 (33) 2477.414 (34) 2496.769 (35) 2503 …”

Section: The 72-bar Spatial Truss Exampleunclassified

Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

Hu³

et al. 2017

Mathematical Problems in Engineering

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Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short) is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.

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Section: The 72-bar Spatial Truss Exampleunclassified

Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

Hu³

et al. 2017

Mathematical Problems in Engineering

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“…Considered initially for combinatorial problems (Dorigo and Gambardella, 1997), it has been extended to continuous domain (Blum, 2005;Socha and Dorigo, 2008), which is our case. ACO has been proposed for structural topology optimization (Kaveh et al, 2008;Luh and Lin, 2009) but, to the authors knowledge, not yet considered for the optimization of a compliant mechanism.…”

Section: Ant Colony Optimization For Compliant Mechanismsmentioning

confidence: 99%

Compliant mechanisms for an active cardiac stabilizer: lessons and new requirements in the design of a novel surgical tool

et al. 2011

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Abstract. In this paper, three aspects of the use of compliant mechanisms for a new surgical tool, an active cardiac stabilizer, are outlined. First, the interest of compliant mechanisms in the design of the stabilizer is demonstrated with in vivo experimental evaluation of the efficiency of a prototype. We then show that the specific surgical constraints lead to the development of compliant mechanisms, with the design of new original mechanical amplifiers. Finally, the requirements in the design of stabilizers exhibiting a higher level of integration are outlined. Novel architectures and design procedures are actually needed, and we introduce an exploratory study with a proof-of-concept designed using the combination of ant colony optimization and classical pseudo rigid body modeling. Relative errors in the estimation of the displacement do not exceed 5 %. The proposed design method constitutes an interesting approach that may be applied more generally to the design of compliant mechanisms.

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“…This shortcoming inspired researchers to explore using the relatively new and innovative evolutionarybased optimization techniques. For example, these methods have been used recently to address structural engineering optimization problems: Shuffled Complex Evolution Optimizer (SCEO), Ant Colony Optimization (ACO), the Genetic Algorithms (GA), and Particle Swarm Optimizer (PSO) (e.g., [16][17][18][19][20][21][22][23][24]). …”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Optimization of Support Structures for Offshore Wind Turbines Using Genetic Algorithm with Domain‐Trimming

AlHamaydeh

Barakat

Nasif

2017

Mathematical Problems in Engineering

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The powerful genetic algorithm optimization technique is augmented with an innovative "domain-trimming" modification. The resulting adaptive, high-performance technique is called Genetic Algorithm with Domain-Trimming (GADT). As a proof of concept, the GADT is applied to a widely used benchmark problem. The 10-dimensional truss optimization benchmark problem has well documented global and local minima. The GADT is shown to outperform several published solutions. Subsequently, the GADT is deployed onto three-dimensional structural design optimization for offshore wind turbine supporting structures. The design problem involves complex least-weight topology as well as member size optimizations. The GADT is applied to two popular design alternatives: tripod and quadropod jackets. The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. The considered design variables are the truss members end node coordinates, as well as the cross-sectional areas of the truss members, whereas the constraints are the maximum stresses in members and the maximum displacements of the nodes. These constraints are managed via dynamically modified, nonstationary penalty functions. The structures are subject to gravity, wind, wave, and earthquake loading conditions. The results show that the GADT method is superior in finding best discovered optimal solutions.

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Structural topology optimization using ant colony optimization algorithm

Cited by 79 publications

References 35 publications

Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

Size and Topology Optimization for Trusses with Discrete Design Variables by Improved Firefly Algorithm

Compliant mechanisms for an active cardiac stabilizer: lessons and new requirements in the design of a novel surgical tool

Optimization of Support Structures for Offshore Wind Turbines Using Genetic Algorithm with Domain‐Trimming

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