Flower Pollination Algorithm with Fuzzy Approach for Solving Optimization Problems

Valenzuela, Luis; Valdez, Fevrier; Melín, Patricia

doi:10.1007/978-3-319-47054-2_24

Cited by 18 publications

(11 citation statements)

References 11 publications

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“…In 2019, Ramadas and Abraham [17] proposed a flower pollination search strategy algorithm with differential evolution; Zhang et al [18] used FPA to optimize the trend of uncertain renewable energy [18]; and Deepa and Rasi [19] improved the global biological cross-pollination algorithm based on an evolutionary strategy, and used the resulting method for color image segmentation. [20]- [24], but is typically described by a complex model with limited optimization ability. The algorithm also suffers from slow convergence and easily becomes trapped around local optima.…”

Section: And Obtain New Solution X I Elsementioning

confidence: 99%

Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm

2019

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The flower pollination algorithm is a new metaheuristic optimization technique that simulates the pollination behavior of flowers in nature. The global and local search processes of the algorithm are performed by simulating the self-pollination and cross-pollination of flowers. However, the conventional flower pollination algorithm has several limitations. To overcome the problem of slow convergence and prevent the algorithm from becoming stuck around local optimum, this paper describes an enhanced metaheuristic wind-driven flower pollination algorithm (WDFPA). Experiments are conducted using 29 benchmark test functions and two engineering design problems, and the proposed WDFPA is compared against other metaheuristic optimization algorithms and several classical optimization approaches. The results show that WDFPA achieves better performance than the conventional flower pollination algorithm, especially in highdimensional optimization problems. The convergence speed and accuracy of WDFPA exhibit significant improvements over other metaheuristic algorithms in many of the test cases. Additionally, WDFPA produces optimal results for engineering design problems involving a welded beam and a spring structure.INDEX TERMS Enhanced metaheuristic optimization, flower pollination algorithm, wind driven, winddriven flower pollination algorithm.

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Section: And Obtain New Solution X I Elsementioning

confidence: 99%

Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm

2019

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“…The hybrid of a fuzzy technique with FPA is applied to accept possibility that uses various methods for accommodating variation in mutually local and global pollination [18]. The FPA outperforms than its hybridized fuzzy version.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Terms used in HBFPA are explained in Table 4 and probability value is taken as (0.5) in HBFPA. Fitness in HBFPA is calculated using Equations (17) and (18):…”

Section: Hbfpamentioning

confidence: 99%

Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids

et al. 2018

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Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme to accomplish the electricity demand of automated appliances. Recently, many Demand Side Management (DSM) schemes have been explored to alleviate Electricity Cost (EC) and Peak to Average Ratio (PAR). In this paper, energy consumption problem in a residential area is considered. To solve this problem, a heuristic based DSM technique is proposed to minimize EC and PAR with affordable user’s Waiting Time (WT). In heuristic techniques: Bacterial Foraging Optimization Algorithm (BFOA) and Flower Pollination Algorithm (FPA) are implemented.

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“…Despite this simplification, the problem remains very difficult. A molecule with as few as 30 atoms has 2 27 = 134,217,728 local minimizers.…”

Section: Molecular Potential Energy Functionmentioning

confidence: 99%

“…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 with Fuzzy Approach for Solving Optimization Problems

Cited by 18 publications

References 11 publications

Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm

Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm

Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids

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

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