A novel teaching-learning based optimization approach for design of broad-band anti-reflection coatings

Patel, Sankita J.; Toshniwal, Aditi; Kheraj, Vipul

doi:10.1016/j.swevo.2016.12.003

Cited by 9 publications

(4 citation statements)

References 46 publications

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“…Genetic algorithm (GA) is excellent at searching large, complex, and nonlinear solution spaces, making it particularly suitable for the optimization of multilayer optical films, and has been widely applied in various designs of anti-reflection films. 14,[53][54][55] The simulation flow of the GA in this model can be found in Fig. 2(b).…”

Section: Design Of Three-layer Gradient Refractive Index Transparent ...mentioning

confidence: 99%

Modeling of the synergistic anti-reflection effect in gradient refractive index films integrated with subwavelength structures for photothermal conversion

Wang,

Shi,

Liu

et al. 2024

Phys. Chem. Chem. Phys.

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Section: Design Of Three-layer Gradient Refractive Index Transparent ...mentioning

confidence: 99%

Modeling of the synergistic anti-reflection effect in gradient refractive index films integrated with subwavelength structures for photothermal conversion

Wang,

Shi,

Liu

et al. 2024

Phys. Chem. Chem. Phys.

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“…But, in classroom learning paradigm, a learner can also enhance its skill by acquiring the knowledge from other learners 22 . It depends on the acquired knowledge through the teacher and learns from the classmates 42 . The group of learners also called class.…”

Section: Chaotic Teaching Learning Based Optimizationmentioning

confidence: 99%

Chaos teaching learning based algorithm for large‐scale global optimization problem and its application

Shukla

2021

Concurrency and Computation

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Teaching learning‐based optimization (TLBO) is a popular stochastic algorithm that has recently been widely applied in a variety of optimization problems since its start. In TLBO algorithm, the concept of chaos not only shows a vital effect in its convergence but also plays a substantial role to balance of exploration and exploitation through evolution. However, TLBO is quickly trapped in local optima and premature convergence seems when applied to sophisticated complex functions. To handle these problems, we introduced an improved TLBO algorithm using chaotic concept. To achieve ability to search for exploration and exploitation, new phase called chaotic phase is added in original TLBO algorithm. The proposed method is thoroughly evaluated on benchmark test suites. The numerical result show that proposed method is relatively effective in adapting the chaotic value regarding original TLBO in terms of solution quality and convergence rate. In addition, performance of proposed method is evaluated on benchmark KDD Cup 99 intrusion dataset. The experimental results demonstrate that proposed method achieves higher predictive accuracy, detection rate, false alarm rate, and provided more significant features as compared with other wrapper techniques.

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“…It is seen that combination of TLBO-TS algorithm provides faster convergence than TLBO and TS algorithms. Patel et al have applied teaching-learning based optimization (TLBO) to design ultra-low reflective coating over a broad wavelength-band using multilayer thin-film structures for optoelectronic devices [38]. The results of TLBO algorithm are compared with GA using Wilcoxon singed ranked test.…”

Section: Related Workmentioning

confidence: 99%

A New Variant of Teaching Learning Based Optimization Algorithm for Global Optimization Problems

Kumar

Dahiya²,

Malik³

et al. 2019

IJCAI

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This paper presents a new variant of teaching learning based optimization (TLBO) algorithm for solving global optimization problems. The performance of the TLBO algorithm depends on coordination of teacher phase and learner phase. It is noticed that sometimes performance of TLBO algorithm is affected due to lack of diversity in teacher and learner phases. In this work, a new variant of TLBO algorithm is proposed based on genetic crossover and mutation strategies. These strategies are inculcated in TLBO algorithm for improving its search mechanism and convergence rate. Genetic mutation strategy is applied in teacher phase of TLBO algorithm for improving the mean knowledge of leaners. While, Crossover strategy is applied in learner phase of TLBO algorithm to find the good learner. The effectiveness of the proposed algorithm is tested on several bench mark test functions of CEC'14. From simulation results, it is stated that the proposed algorithm provides more optimized results in comparison to same class of algorithms.Povzetek: V prispevku je opisan nov globalni optimizacijski algoritem na osnovi učenja optimizacije (TLBO).

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A novel teaching-learning based optimization approach for design of broad-band anti-reflection coatings

Cited by 9 publications

References 46 publications

Modeling of the synergistic anti-reflection effect in gradient refractive index films integrated with subwavelength structures for photothermal conversion

Modeling of the synergistic anti-reflection effect in gradient refractive index films integrated with subwavelength structures for photothermal conversion

Chaos teaching learning based algorithm for large‐scale global optimization problem and its application

A New Variant of Teaching Learning Based Optimization Algorithm for Global Optimization Problems

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