A parallel GWO technique for aligning multiple molecular sequences

Jayapriya, J.; Arock, Michael

doi:10.1109/icacci.2015.7275611

Cited by 18 publications

(9 citation statements)

References 15 publications

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“…Several algorithms have also been developed to improve the convergence performance of Grey Wolf Optimizer that includes parallelized GWO [22,23], binary GWO [24], integration of DE with GWO [25], hybrid GWO with Genetic Algorithm (GA) [26], hybrid DE with GWO [27], and hybrid Grey Wolf Optimizer using Elite Opposition Based Learning Strategy and Simplex Method [28].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

Singh

2017

Journal of Applied Mathematics

228

143

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A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). The main idea is to improve the ability of exploitation in Particle Swarm Optimization with the ability of exploration in Grey Wolf Optimizer to produce both variants' strength. Some unimodal, multimodal, and fixeddimension multimodal test functions are used to check the solution quality and performance of HPSOGWO variant. The numerical and statistical solutions show that the hybrid variant outperforms significantly the PSO and GWO variants in terms of solution quality, solution stability, convergence speed, and ability to find the global optimum.

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Section: Introductionmentioning

confidence: 99%

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

Singh

2017

Journal of Applied Mathematics

228

143

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“…In 2015, Bodenhofer et al, [23] developed an R package for mu ltip le sequence alignment. Jayapriya et al, in 2015 [24] proposed a parallel approach using Grey Wolf Optimizer technique for sequence align ment problem.…”

Section: Related Workmentioning

confidence: 99%

“…The structure of a DNA is shown in Figure 2. The DNA hybrid izat ion is a process that has different operations like denaturing and annealing [24] in DNA computing. These operations are used in this work for distance calculation.…”

Section: A Dna Structure and Its Operationsmentioning

confidence: 99%

A Novel Distance Metric for Aligning Multiple Sequences Using DNA Hybridization Process

Jayapriya¹,

Arock

2016

IJISA

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This paper elucidates a new approach for aligning mult iple sequences using DNA operations. A new distance measure using DNA hybridization melt ing temperature that gives appro ximate solutions for the mu ltip le sequence alignment (MSA) problem is proposed. This paper provides proof for the proposed distance measure using the distance function properties. With this distance metric, a d istance measure is constructed that generates a guide tree for the align ment. Prov iding an accurate solution in less computational t ime is considered to be a challenging task for the MSA problem. Developing an algorith m for the MSA problem is essentially a trade-off between finding an accurate solution and that can be completed in less computational time. In order to reduce the time co mplexity, the Bioinspired technique called the DNA co mputing is applied in calculat ing the distance between the sequences. The main application of this mu ltiple sequence alignment (MSA) is to identify the sub-sequences for the functional study of the whole genome sequences. The detailed theoretical study of this approach is explained in this paper.

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“…GWO has recently been developed and is metaheuristics-inspired from the hunting mechanism and leadership hierarchy of grey wolves in nature and has been successfully applied for solving optimizing key values in the cryptography algorithms [1], feature subset selection [2], time forecasting [3], optimal power flow problem [4], economic dispatch problems [5], flow shop scheduling problem [6] and optimal design of double later grids [7]. Several algorithms have also been developed to improve the convergence performance of GWO that includes parallelized GWO [8,9], a hybrid version of GWO with PSO [10] and binary GWO [11].…”

Section: Introductionmentioning

confidence: 99%

A New Hybrid Whale Optimizer Algorithm with Mean Strategy of Grey Wolf Optimizer for Global Optimization

Singh

Hachimi

2018

MCA

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Abstract:The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO) and Whale Optimizer Algorithm (WOA). We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO) algorithm: (i) firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii) secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.

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A parallel GWO technique for aligning multiple molecular sequences

Cited by 18 publications

References 15 publications

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance

A Novel Distance Metric for Aligning Multiple Sequences Using DNA Hybridization Process

A New Hybrid Whale Optimizer Algorithm with Mean Strategy of Grey Wolf Optimizer for Global Optimization

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