Flower Pollination Algorithm for Multimodal Optimization

Gálvez, Jorge; Cuevas, Erik; Ávalos, Omar

doi:10.2991/ijcis.2017.10.1.42

Cited by 27 publications

(22 citation statements)

References 28 publications

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“…In this section, we will present a brief description of the Multimodal Flower Pollination Algorithm (MFPA), proposed by Gálvez et al (2017). The original Flower Pollination Algorithm (FPA) was proposed by Yang (2012) and mimics the process of flower pollination.…”

Section: Methodsmentioning

confidence: 99%

“…At the end, the best solution found is a potential global optimum. Gálvez et al (2017) proposed a multimodal flower pollination algorithm (MFPA) enhancing the original algorithm with multimodal capabilities, in which they added the process of finding the global optimum and multiple local optima. In the MFPA, three new elements are included.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, the switch probability (between global and local pollination) was 0,25, the population size was fixed in 50 individuals and the number of iterations (stopping criterion) was 500. These are the same parameters proposed by Gálvez et al (2017). In fact, we are using the same set of parameters presented in the original algorithm, since a desirable property of any metaheuristic is the ability to deal with different problems without costly and difficult parametrization procedures.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems

et al. 2020

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Multimodal optimization problems are commonly found in engineering problems, and their solution can be very challenging for metaheuristic approaches. In this work, the use of a recently proposed multimodal metaheuristic method was analyzed - the Multimodal Flower Pollination Algorithm - in two fluid phase equilibrium problems: (i) the calculation of double azeotropes and (ii) parameter estimation in a thermodynamic model. Two different formulations were also considered in the double azeotropy problem. In the azeotrope calculation, a statistical analysis was conducted in order to verify if the algorithm performance is affected by the the problem formulation. The computational results indicate that the methodology provides robust results and that the objective function employed affects the computational performance.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems

et al. 2020

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“…Switch probability controls the conversion between global pollination and local pollination. FPA has achieved good results in solving multi-objective optimization problem and other application problems [50][51][52][53]. FPA has robust performance for applications.…”

Section: Training Methods Based On Optimization Of Learning Ratementioning

confidence: 99%

Blister Defect Detection Based on Convolutional Neural Network for Polymer Lithium-Ion Battery

Xie

Zhang

2019

Applied Sciences

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To ensure the quality and reliability of polymer lithium-ion battery (PLB), automatic blister defect detection instead of manual detection is developed in the production of PLB cell sheets. A convolutional neural network (CNN) based detection method is proposed to detect blister in cell sheets employing cell sheet images. An improved architecture for dense block and a learning method based on optimization of learning rate are discussed. The proposed method was superior to other machine learning based methods when the classification performance and confusion matrix were compared in experiments. The proposed CNN method had the best defect detection performance and real-time performance for industry field application. Keywords: defect detection; polymer lithium-ion battery; convolutional neural network; deep learning; blister defect; flower pollination algorithm IntroductionThe application of lithium-ion batteries has changed consumer electronic products, which greatly reduce the weight and volume of mobile phones, notebooks, and other portable products. Lithium-ion batteries have been widely studied, including model, optimal design, and so on [1][2][3][4][5][6]. At present, the most commonly used lithium-ion battery is polymer lithium-ion battery (PLB). The cathode materials of PLB are commonly lithium cobalt acid, lithium manganese acid, ternary materials or lithium iron phosphate. The anode materials usually use carbon materials, such as artificial graphite, natural graphite, intermediate phase carbon microspheres, petcoke, carbon fiber, pyrolysis resin carbon and so on. C-rate is the measurement of the charge and discharge current with respect to its nominal capacity. At present, most PLB use polymer gel electrolyte instead of liquid electrolyte, which makes PLB have the advantages of thinning, arbitrary area and arbitrary shape. These characteristics improve the capacity of PLB, and PLB has the characteristics of miniaturization, thinning, and light quantification. PLB has been widely used in portable electronic equipment, and it is gradually being applied to more fields. With the application of PLB in more and more electronic products, the quality of PLB has more and more influence on the quality of electronic products. The quality of PLB is critical to the quality and reliability of electronic products.Recently, an automatic line of PLB has been developed in Dongsheng Energy Corporation, Weihai, China. The PLB has a voltage of 48 V, a charging current of 2-3 A, and nominal capacity of 16 AH. The anode of PLB is a conductive high molecular polymer, the catrode is graphite, and a colloidal polymer electrolyte is used. During the production process of the PLB, several cathode pieces, anode pieces, and separator pieces are combined to produce a cell sheet. Great battery capacity can be provided with more cell sheets combined together. Thus, the quality inspection of cell sheets in automated production lines is essential to the quality of the final battery product. The cell sheet defect needs to be detected to ens...

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“…This paper studies an approach based on flower pollination, namely Flower Pollination Algorithm (FPA) proposed in 2012 by Xin-She Yang [21] in order to solve the energy minimization problems. Although many researchers are applied the FPA to solve many optimization problems such as [22][23][24][25][26][27] it suffers from the premature convergence and it may get trapped in local minima especially when it applies to solve large scale global optimization problem such as the problem of minimization of potential energy function. In order to solve the problem of the premature convergence of the FPA, we propose a new hybrid flower pollination algorithm and genetic algorithm in order to solve the molecular potential energy function minimizations.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Flower Pollination and Genetic Algorithm for Minimizing the Non-Convex Potential Energy of Molecular Structure

Tawhid¹,

Ali²

2017

Trends Artif Intell

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Minimizing the molecular potential energy function is a real-life problem which can help to predict the threedimensional structure of the protein by knowing its steady state of the molecules. In this paper, we propose a new hybrid algorithm by combining the flower pollination algorithm and the genetic algorithm in order to minimize a simplified model of the energy function of the molecule. The proposed algorithm is called Hybrid Flower Pollination and Genetic Algorithm. We use the flower pollination algorithm to balance between the exploration and the exploitation process in the proposed algorithm. Also, we divide the population into subpopulations and applying the arithmetical crossover operator in each sub-population in order to increase the diversity of the search in the algorithm. Further, we apply the genetic mutation operator in the whole population in order to avoid the premature convergence and avoid trapping in local minima. Moreover, we compare the proposed algorithm against 3 benchmark algorithms, in order to investigate its efficiency. The numerical experiment results show that the proposed algorithm is a promising and efficient algorithm and can obtain the global minimum or near global minimum of the molecular energy function of the simplified model with up to 200 degrees of freedom faster than the other comparative algorithms.

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Flower Pollination Algorithm for Multimodal Optimization

Cited by 27 publications

References 28 publications

Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems

Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems

Blister Defect Detection Based on Convolutional Neural Network for Polymer Lithium-Ion Battery

A Hybrid Flower Pollination and Genetic Algorithm for Minimizing the Non-Convex Potential Energy of Molecular Structure

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