A hybrid OC–GA approach for fast and global truss optimization with frequency constraints

Zuo, Wenjie; Bai, Jiantao; Li, Bin

doi:10.1016/j.asoc.2013.09.002

Cited by 53 publications

(11 citation statements)

References 29 publications

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“…This is a benchmark problem that was extensively studied by many authors using different optimization methods [33][34][35][36][37][38][39][40][41][42]. Several of the best designs found in the literature are detailed in Table 1.…”

Section: Design Variablesmentioning

confidence: 99%

“…The effectiveness of the SGA is demonstrated through a selection of benchmark problems taken from the literature. Special attention is given to problems that involve topology optimization and natural frequency constraints [33][34][35][36][37][38][39][40][41][42] due to the complexities that they present. The first two problems consist in the size and size/shape optimization of truss structures with natural frequency constraints.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Search group algorithm: A new metaheuristic method for the optimization of truss structures

Gonçalves

López

Miguel

2015

Computers & Structures

170

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Section: Design Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Search group algorithm: A new metaheuristic method for the optimization of truss structures

Gonçalves

López

Miguel

2015

Computers & Structures

170

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“…Kaveh and Zolghadr [23] developed a hybridized CSS-BBBC algorithm with trap recognition capability for truss layout optimization. Zuo et al [24] proposed a hybrid OC-GA approach for fast and global truss layout optimization; Kaveh and Javadi [25] used harmony search and ray optimizer to enhance the PSO algorithm to optimize truss layout under multiple frequency constraints; Liu and Ye [26] designed a genetic simulated annealing algorithm for domes layout optimization. Gholizadeh [17] proposed a hybridized cellular automata and PSO algorithm for truss layout optimization.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Xiao

Wang

Sun

et al. 2014

Mathematical Problems in Engineering

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Due to the fact that vastly different variables and constraints are simultaneously considered, truss layout optimization is a typical difficult constrained mixed-integer nonlinear program. Moreover, the computational cost of truss analysis is often quite expensive. In this paper, a novel fitness estimation based particle swarm optimization algorithm with an adaptive penalty function approach (FEPSO-AP) is proposed to handle this problem. FEPSO-AP adopts a special fitness estimate strategy to evaluate the similar particles in the current population, with the purpose to reduce the computational cost. Further more, a laconic adaptive penalty function is employed by FEPSO-AP, which can handle multiple constraints effectively by making good use of historical iteration information. Four benchmark examples with fixed topologies and up to 44 design dimensions were studied to verify the generality and efficiency of the proposed algorithm. Numerical results of the present work compared with results of other state-of-the-art hybrid algorithms shown in the literature demonstrate that the convergence rate and the solution quality of FEPSO-AP are essentially competitive.

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“…Here, NHPGA combined the advantage of simplex search, parallel computing and genetic algorithm with niche technique for getting effective and efficient solution. Zuo et al [59] for obtaining global solution and to speed up convergence of truss optimization problems used genetic algorithm and hybrid optimality criterion algorithm with multiple frequency constraints.…”

Section: Introductionmentioning

confidence: 99%

Modified symbiotic organisms search for structural optimization

Kumar

Tejani²,

Mirjalili

2018

Engineering with Computers

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The structural dynamic response predominantly depends upon natural frequencies which fabricate these as a controlling parameter for dynamic response of the truss. However, truss optimization problems subjected to multiple fundamental frequency constraints with shape and size variables are more arduous due to its characteristics like non-convexity, nonlinearity, and implicit with respect to design variables. In addition, mass minimization with frequency constraints are conflicting in nature which intricate optimization problem. Using meta-heuristic for such kind of problem requires harmony between exploration and exploitation to regulate the performance of the algorithm. This paper proposes a modification of a nature inspired Symbiotic Organisms Search (SOS) algorithm called a Modified SOS (MSOS) algorithm to enhance its efficacy of accuracy in search (exploitation) together with exploration by introducing an adaptive benefit factor and modified parasitism vector. These modifications improved search efficiency of the algorithm with a good balance between exploration and exploitation, which has been partially investigated so far. The feasibility and effectiveness of proposed algorithm is studied with six truss design problems. The results of benchmark planar/space trusses are compared with other meta-heuristics. Complementarily the feasibility and effectiveness of the proposed algorithms are investigated by three unimodal functions, thirteen multimodal functions, and six hybrid functions of the CEC2014 test suit. The experimental results show that MSOS is more reliable and efficient as compared to the basis SOS algorithm and other state-of-the-art algorithms. Moreover, the MSOS algorithm provides competitive results compared to the existing meta-heuristics in the literature.

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A hybrid OC–GA approach for fast and global truss optimization with frequency constraints

Cited by 53 publications

References 29 publications

Search group algorithm: A new metaheuristic method for the optimization of truss structures

Search group algorithm: A new metaheuristic method for the optimization of truss structures

Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Modified symbiotic organisms search for structural optimization

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