DE-FPA: A hybrid differential evolution-flower pollination algorithm for function minimization

Chakraborty, Dwaipayan; Saha, Sankhadip; Dutta, Oindrilla

doi:10.1109/ichpca.2014.7045350

Cited by 45 publications

(21 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many FPA hybridization variants have also been proposed in the literature, including the chaotic HS for solving Sudoku puzzles [ 52 ], FPA with GA for solving constrained optimization problems [ 53 ], FPA with PSO (FPAPSO) for solving constrained global optimization problems [ 54 ], FPA with TS for solving unconstrained optimization problems [ 55 ], FPA with DE (DE-FPA) to overcome the drawbacks of slow convergence to global optima [ 56 ], FPA with clonal selection algorithm [ 57 ], and FPA with artificial bees and biogeography optimization algorithm for satellite image classification [ 58 ]. Recently, DE-FPA has also been integrated with the time-varying fuzzy selection mechanism to find the optimal dispatch of wind—thermal dynamic multi-objective problems [ 25 ].…”

Section: Flower Pollination Algorithmmentioning

confidence: 99%

Hybrid flower pollination algorithm strategies for t-way test suite generation

et al. 2018

View full text Add to dashboard Cite

The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size.

show abstract

Section: Flower Pollination Algorithmmentioning

confidence: 99%

Hybrid flower pollination algorithm strategies for t-way test suite generation

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Inspired from such features of the pollination process, the FPA is formulated as an optimization algorithm in which biotic pollination and cross-pollination act as global search; abiotic pollination and self-pollination are utilized as local search (see figure 2) [25]. Compared with other nature-inspired algorithms, the FPA possesses a promising capability of global search [41][42][43][44]. In the FPA, a solution x in the search space represents a flower.…”

Section: Fpamentioning

confidence: 99%

Estimation of algal colonization growth on mortar surface using a hybridization of machine learning and metaheuristic optimization

Tran

Hoang

2017

Sādhanā

View full text Add to dashboard Cite

Estimation of the algal colonization growth on façade structure can provide useful information for the task of building maintenance. This research proposes a machine learning method based on the least squares support vector regression (LS-SVR) for modelling the growth time of the green alga Klebsormidium flaccidum on mortar surfaces. Furthermore, to identify an appropriate set of the LS-SVR hyper-parameters, the flower pollination algorithm (FPA) is employed as an optimization technique. The characteristics of the mortar samples, including surface roughness, porosity, surface pH, carbonated condition and type of cement, are employed as input factors for the analysing process. This study relies on a dataset that records 539 laboratory experiments to establish a hybrid model of the LS-SVR and the FPA. The cross-validation process reveals that the proposed method can successfully capture the functional relationship between the algal colonization growth and its influencing factors with a satisfactory outcome (the coefficient of determination R 2 = 0.94 and the root mean square error RMSE = 4.55). These facts demonstrate that the hybrid model is a promising tool for assisting the decision-making process in building maintenance planning.

show abstract

“…We categorise them into 4 classes: (1) The works proposed by Yang and his co-authors [18,[22][23][24][25], (2) the works just applying the FPA for solving optimisation problems [27][28][29][30], (3) FPA extensions [31][32][33][34][35] and (4) the works analysing the FPA performances [36][37][38]. These contributions are analysed with greater detail in the next section.…”

Section: The Choice Between Local Pollination and Global Pollination Ismentioning

confidence: 99%

“…In addition, the founding works of Yang [18,[22][23][24][25], from which the theoretical description of the FPA is extracted, are missing in the bibliography, another reference is provided for the whole part which is copied from [18]. Publication 13 [34]: The FPA is hybridised, in this work, with differential evolution [34]. The resulting hybrid is validated by applying it on some benchmark functions.…”

Section: Publication 10 [31]mentioning

confidence: 99%