Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

Pholdee, Nantiwat; Bureerat, Sujin

doi:10.1016/j.advengsoft.2014.04.005

Cited by 87 publications

(28 citation statements)

References 35 publications

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“…This provides the possibility of hybridizing SCA with a differential evolution (DE) technique that is efficient for structural damage detection problems. A broad‐ ranging application and development of metaheuristic optimizations in solving other engineering problems are demonstrated in previous studies …”

Section: Introductionmentioning

confidence: 95%

“…A broad-ranging application and development of metaheuristic optimizations in solving other engineering problems are demonstrated in previous studies. [28][29][30][31][32][33][34] The goal of this study is to enhance dent damage detection of tubular jacket braced and leg members through an adaptive optimization algorithm. By following back to the research conducted previously, the ASCA-DE is adopted and combined with the parameter separation technique to be called as ASCA-DE-ps.…”

Section: Introductionmentioning

confidence: 99%

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A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

Punurai

Azad

Pholdee

et al. 2019

Computational Intelligence

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Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross‐sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts. The lateral impacts can be due to ship collisions or through the impact of falling objects. The impact forces can weaken some members that influence the overall performance of the platform. This demonstrates an urgent need to develop a framework that can accurately forecast dent depth as well as dent angle of the affected members. This study investigates the use of an adaptive metaheuristics algorithm to provide automatic detection of denting damage in an offshore structure. The damage information includes dent depth and the dent angle. A model is developed in combination with the percentage of the dent depth of the damaged member and is used to assess the performance of the method. It demonstrates that small changes in stiffness of individual damaged bracing members are detectable from measurements of global structural motion.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

Punurai

Azad

Pholdee

et al. 2019

Computational Intelligence

Self Cite

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“…Moreover, the parallel FWA on Graphic Processor Unit has also been proposed [12]. For the applications, FWA has been used for digital filters design [6], non-negative [13], pattern recognition [14], spam detection [15], network reconfiguration [16], [17], truss mass minimisation [18], clustering [19] and so on.…”

Section: Introductionmentioning

confidence: 99%

S-metric based multi-objective fireworks algorithm

Zheng

Tan

2015

2015 IEEE Congress on Evolutionary Computation (CEC)

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Fireworks Algorithm(FWA) is a recently developed swarm intelligence algorithm for single objective optimization problems which gains very promising performances in many areas. In this paper, we extend the original FWA to solve multi-objective optimization problems with the help of S-metric. The S-metric is a frequently used quality measure for solution sets comparison in evolutionary multi-objective optimization algorithms (EMOAs). Besides, S-metric can also be used to evaluate the contribution of a single solution among the solution set. Traditional multi-objective optimization algorithms usually perform a (μ + 1) strategy and update the external archive one by one, while the proposed S-metric based multi-objective fireworks algorithm(S-MOFWA) performs a (μ + μ) strategy, thus converging faster to a set of pareto solutions by three steps: 1)Exploring the solution space by mimicking the explosion of fireworks; 2)Performing a simple selection strategy for choosing the next generation of fireworks according to their S-metric; 3)Utilizing an external archive to maintain the best solution set ever found, with a new archive definition and a novel updating strategy, which can update the archive with μ solutions in a single process. The experimental results on benchmark functions suggest that the proposed S-MOFWA outperforms three other well-known algorithms, i.e. NSGA-II, SPEA2 and PESA2 in terms of the convergence measure and covered space measure.

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“…Based on the analysis of each operator of the fireworks algorithm, an improvement of fireworks algorithm (IFWA) [5] was proposed. Since the FWA was proposed, it has been applied to many areas [6], including digital filter design [7], nonnegative matrix factorization [8], spam detection [9], image identification [10], mass minimization of trusses with dynamic constraints [11], clustering [12], power loss minimization and voltage profile enhancement [13], etc.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Mutation Dynamic Search Fireworks Algorithm

Han

Zhao

et al. 2017

Algorithms

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Abstract:The Dynamic Search Fireworks Algorithm (dynFWA) is an effective algorithm for solving optimization problems. However, dynFWA easily falls into local optimal solutions prematurely and it also has a slow convergence rate. In order to improve these problems, an adaptive mutation dynamic search fireworks algorithm (AMdynFWA) is introduced in this paper. The proposed algorithm applies the Gaussian mutation or the Levy mutation for the core firework (CF) with mutation probability. Our simulation compares the proposed algorithm with the FWA-Based algorithms and other swarm intelligence algorithms. The results show that the proposed algorithm achieves better overall performance on the standard test functions.

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Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

Cited by 87 publications

References 35 publications

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross‐sectional dent damaged offshore platform members

S-metric based multi-objective fireworks algorithm

Adaptive Mutation Dynamic Search Fireworks Algorithm

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