Relevant bibliographies by topics / Flower Pollination Optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Flower Pollination Optimization'

Author: Grafiati
Published: 3 June 2025
Last updated: 20 July 2025

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Journal articles on the topic "Flower Pollination Optimization"

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Strelin, Marina M., Federico Sazatornil, Santiago Benitez-Vieyra, and Mariano Ordano. "Bee, hummingbird, or mixed-pollinated Salvia species mirror pathways to pollination optimization: a morphometric analysis based on the Pareto front concept." Botany 95, no. 2 (2017): 139–46. http://dx.doi.org/10.1139/cjb-2016-0145.

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Optimization of flower phenotypes to ensure pollination by agents differing in their match with fertile flower structures can involve fitness trade-offs if the aspects of the phenotype that enhance the fitness contribution of one pollinator are detrimental for pollination by the other agents. If these trade-offs are substantial, flower optimization for specialized pollination is expected. However, optimization for generalized pollination may also take place in trade-off scenarios, as long as the joint contribution of two or more types of pollinators to global pollination fitness is greater tha
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Syafruddin, Willa Ariela, Rio Mukhtarom Paweroi, and Mario Köppen. "Behavior Selection Metaheuristic Search Algorithm for the Pollination Optimization: A Simulation Case of Cocoa Flowers." Algorithms 14, no. 8 (2021): 230. http://dx.doi.org/10.3390/a14080230.

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Since nature is an excellent source of inspiration for optimization methods, many optimization algorithms have been proposed, are inspired by nature, and are modified to solve various optimization problems. This paper uses metaheuristics in a new field inspired by nature; more precisely, we use pollination optimization in cocoa plants. The cocoa plant was chosen as the object since its flower type differs from other kinds of flowers, for example, by using cross-pollination. This complex relationship between plants and pollinators also renders pollination a real-world problem for chocolate prod
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Zhou, Haili, Junlang Ou, Penghao Meng, Junhua Tong, Hongbao Ye, and Zhen Li. "Reasearch on Kiwi Fruit Flower Recognition for Efficient Pollination Based on an Improved YOLOv5 Algorithm." Horticulturae 9, no. 3 (2023): 400. http://dx.doi.org/10.3390/horticulturae9030400.

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A close relationship has been observed between the growth and development of kiwi fruit and the pollination of the kiwi flower. Flower overlap, flower tilt, and other problems will affect this plant’s pollination success rate. A pollination model based on YOLOv5 was developed to improve the pollination of kiwi flowers. The K-means++ clustering method was used to cluster the anchors closer to the target size, which improved the speed of the algorithm. A convolutional block module attention mechanism was incorporated to improve the extraction accuracy with respect to kiwi flower features and eff
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Xu, Wenhao, Zhicheng Ji, and Yan Wang. "A flower pollination algorithm for flexible job shop scheduling with fuzzy processing time." Modern Physics Letters B 32, no. 34n36 (2018): 1840113. http://dx.doi.org/10.1142/s0217984918401139.

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Considering the uncertainty in real manufacturing workshops, the fuzzy flexible job shop scheduling problem (fFJSP) is addressed, in which the triangular fuzzy number is used to represent the processing time. A discrete flower pollination algorithm (DFPA) is proposed in this paper to minimize the maximum fuzzy completion time. Flower pollination algorithm (FPA) is inspired by the pollination process of flowering plants, which realizes global search and local search by means of cross-pollination and self-pollination of flowers in nature. DFPA extends to FPA by introducing discrete operator duri
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Gálvez, Jorge, Erik Cuevas, and Omar Avalos. "Flower Pollination Algorithm for Multimodal Optimization." International Journal of Computational Intelligence Systems 10, no. 1 (2017): 627. http://dx.doi.org/10.2991/ijcis.2017.10.1.42.

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Hulens, Dries, Wiebe Van Ranst, Ying Cao, and Toon Goedemé. "Autonomous Visual Navigation for a Flower Pollination Drone." Machines 10, no. 5 (2022): 364. http://dx.doi.org/10.3390/machines10050364.

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In this paper, we present the development of a visual navigation capability for a small drone enabling it to autonomously approach flowers. This is a very important step towards the development of a fully autonomous flower pollinating nanodrone. The drone we developed is totally autonomous and relies for its navigation on a small on-board color camera, complemented with one simple ToF distance sensor, to detect and approach the flower. The proposed solution uses a DJI Tello drone carrying a Maix Bit processing board capable of running all deep-learning-based image processing and navigation alg
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Srikanth, Kavirayani, and Nagesh Kumar GV. "Flower Pollination for Rotary Inverted Pendulum Stabilization with Delay." TELKOMNIKA Telecommunication, Computing, Electronics and Control 15, no. 1 (2017): 245–53. https://doi.org/10.12928/TELKOMNIKA.v15i1.3403.

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Flower pollination is a single objective optimization technique which as a unconstrained optimization method is applied for the stabilization of the rotary inverted pendulum system. It was observed that the flower pollination method gave better sensitivity in control of the pendulum about its upright unstable equilibrium position with less time and definitely indicated that the method is an energy efficient method when compared with other methods like direct pole placement. This method yielded results under the influence of time delay and have proven that the influence of time delay is signifi
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Franceschinelli, Edivani Villaron. "The pollination biology of two species of Helicteres (Malvaceae) with different mechanisms of pollen deposition." Flora 200 (June 5, 2005): 65–73. https://doi.org/10.5281/zenodo.13406709.

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(Uploaded by Plazi for the Bat Literature Project) Species of Helicteres are pollinated mainly by hummingbirds and bats. Most species pollinated by hummingbirds have a mechanism of depositing pollen on the top of the pollinator's head such as is shown in this work for Helicteres sacarolha. H. brevispira has an unusual mechanism of depositing pollen grains under the tail or on the abdomen of the hummingbirds. The top of the birds' head may be considered an efficient place to transport pollen grains, because it is plain, easily accessible for deposition and donation of pollen and not easily acce
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Mehta, Ishita, Geetika Singh, Yogita Gigras, Anuradha Dhull, and Priyanka Rastogi. "Robotic Path Planning Using Flower Pollination Algorithm." Recent Advances in Computer Science and Communications 13, no. 2 (2020): 191–99. http://dx.doi.org/10.2174/2213275911666190320160837.

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Background: Robotic path planning is an important facet of robotics. Its purpose is to make robots move independently in their work environment from a source to a destination whilst satisfying certain constraints. Constraint conditions are as follows: avoiding collision with obstacles, staying as far as possible from the obstacles, traversing the shortest path, taking minimum time, consuming minimum energy and so on. Hence, the robotic path planning problem is a conditional constraint optimization problem. Methods: To overcome this problem, the Flower Pollination Algorithm, which is a metaheur
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Afiahayati, Yap Bee Wah, Sri Hartati, et al. "Forecasting the Cumulative COVID-19 Cases in Indonesia Using Flower Pollination Algorithm." Computation 10, no. 12 (2022): 214. http://dx.doi.org/10.3390/computation10120214.

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Coronavirus disease 2019 (COVID-19) was declared as a global pandemic by the World Health Organization (WHO) on 12 March 2020. Indonesia is reported to have the highest number of cases in Southeast Asia. Accurate prediction of the number of COVID-19 cases in the upcoming few days is required as one of the considerations in making decisions to provide appropriate recommendations in the process of mitigating global pandemic infectious diseases. In this research, a metaheuristics optimization algorithm, the flower pollination algorithm, is used to forecast the cumulative confirmed COVID-19 cases
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Dissertations / Theses on the topic "Flower Pollination Optimization"

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Neves, Patrícia Silva. "Expansão estática de sistemas de transmissão de energia elétrica via FPA." Universidade Federal de Juiz de Fora (UFJF), 2017. https://repositorio.ufjf.br/jspui/handle/ufjf/6042.

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Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2017-12-22T14:54:33Z No. of bitstreams: 1 patriciasilvaneves.pdf: 1941458 bytes, checksum: 16ab3b743d0b75134d320f08de292905 (MD5)<br>Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-01-22T18:33:39Z (GMT) No. of bitstreams: 1 patriciasilvaneves.pdf: 1941458 bytes, checksum: 16ab3b743d0b75134d320f08de292905 (MD5)<br>Made available in DSpace on 2018-01-22T18:33:39Z (GMT). No. of bitstreams: 1 patriciasilvaneves.pdf: 1941458 bytes, checksum: 16ab3b743d0b75134d320f08de292905 (MD5) Previous issue date:
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Bibiks, Kirils, Jian-Ping Li, and Yim Fun Hu. "Discrete flower pollination algorithm for resource constrained project scheduling problem." 2015. http://hdl.handle.net/10454/9991.

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Yes<br>In this paper, a new population-based and nature-inspired metaheuristic algorithm, Discrete Flower Pollination Algorithm (DFPA), is presented to solve the Resource Constrained Project Scheduling Problem (RCPSP). The DFPA is a modification of existing Flower Pollination Algorithm adapted for solving combinatorial optimization problems by changing some of the algorithm's core concepts, such as flower, global pollination, Lévy flight, local pollination. The proposed DFPA is then tested on sets of benchmark instances and its performance is compared against other existing metaheuristic algor
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Book chapters on the topic "Flower Pollination Optimization"

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Zolghadr-Asli, Babak. "Flower Pollination Algorithm." In Computational Intelligence-based Optimization Algorithms. CRC Press, 2023. http://dx.doi.org/10.1201/9781003424765-19.

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Azad, Marzie, Omid Bozorg-Haddad, and Xuefeng Chu. "Flower Pollination Algorithm (FPA)." In Advanced Optimization by Nature-Inspired Algorithms. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5221-7_7.

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Yang, Xin-She. "Flower Pollination Algorithm for Global Optimization." In Unconventional Computation and Natural Computation. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32894-7_27.

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Dhivya, S., and R. Arul. "Hybrid Flower Pollination Algorithm for Optimization Problems." In Algorithms for Intelligent Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6893-7_65.

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Pringsakul, Noppadol, and Deacha Puangdownreong. "Modified Flower Pollination Algorithm for Function Optimization." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68154-8_18.

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Alyasseri, Zaid Abdi Alkareem, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, and Xin-She Yang. "Variants of the Flower Pollination Algorithm: A Review." In Nature-Inspired Algorithms and Applied Optimization. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67669-2_5.

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Łukasik, Szymon, and Piotr A. Kowalski. "Study of Flower Pollination Algorithm for Continuous Optimization." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11313-5_40.

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Rodrigues, Douglas, Gustavo Henrique de Rosa, Leandro Aparecido Passos, and João Paulo Papa. "Adaptive Improved Flower Pollination Algorithm for Global Optimization." In Nature-Inspired Computation in Data Mining and Machine Learning. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28553-1_1.

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Bhave, Sameer, and Pratosh Bansal. "Global Optimization with Petal Guided Flower Pollination Algorithm." In Advancements in Smart Computing and Information Security. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58604-0_27.

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Kundu, Krishanu, and Narendra Nath Pathak. "Circular Antenna Array Optimization Using Flower Pollination Algorithm." In Advances in Computer, Communication and Control. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3122-0_40.

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Conference papers on the topic "Flower Pollination Optimization"

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Arif, Naeem, Muhammad Mateen Afzal Awan, and Aun Haider. "Hierarchal Optimization of Flower Pollination Algorithm for Solar Photovoltaic Systems." In 2024 Horizons of Information Technology and Engineering (HITE). IEEE, 2024. https://doi.org/10.1109/hite63532.2024.10777230.

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Sreedhar, Gurijala, CH Hussaian Basha, Shaik Rafikiran, Likhitha R, and Faisal Alsaif. "Development of Polymer Fuel Cell System with Improved Flower Pollination Optimization MPPT Controller." In 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE). IEEE, 2025. https://doi.org/10.1109/icdcece65353.2025.11034835.

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Mahankali, Saritha, R. Kesavan, and S. A. Kalaiselvan. "Node Coverage and Connectivity Optimization in Heterogeneous Wireless Sensor Networks Using Improved Flower Pollination Algorithm." In 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS). IEEE, 2024. https://doi.org/10.1109/icuis64676.2024.10866393.

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Kaczmarczyk, Grzegorz, Radosław Stanisławski, Danton Diego Ferreira, Łukasz Knypiński, and Marcin Kamiński. "Optimization based on Flower Pollination Algorithm applied for fuzzy Lyapunov-based speed controller of a drive with elastic connection." In 2024 Progress in Applied Electrical Engineering (PAEE). IEEE, 2024. http://dx.doi.org/10.1109/paee63906.2024.10701447.

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Kuppuraj, T., Paramjit Baxi, Kala Priydarshini G, Mithhil Arora, Rahul Gupta, and Santosh Kumar. "Hybrid Optimization of Data Replication in Mobile Edge Computing using Flower Pollination and Simulated Annealing to Minimize IoT Latency." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911069.

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Dao, Thi-Kien, Tien-Szu Pan, Trong-The Nguyen, Shu-Chuan Chu, and Jeng-Shyang Pan. "A Compact Flower Pollination Algorithm Optimization." In 2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN). IEEE, 2016. http://dx.doi.org/10.1109/cmcsn.2016.30.

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Banerjee, Subhabrata, and Sudipta Chattopadhyay. "Equalizer optimization using Flower Pollination Algorithm." In 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2016. http://dx.doi.org/10.1109/icpeices.2016.7853518.

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Sidi, Hamed Ould, Rachid Ellaia, Emmanuel Pagnacco, and Ahmed Tchvagha Zeine. "Multiobjective Design Optimization using Flower Pollination Algorithm." In 2021 7th International Conference on Optimization and Applications (ICOA). IEEE, 2021. http://dx.doi.org/10.1109/icoa51614.2021.9442651.

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Vijayaraj, S., and R. K. Santhi. "Multi-area economic dispatch using flower pollination algorithm." In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755541.

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Klein, Carlos Eduardo, Emerson Hochsteiner de Vasconcelos Segundo, Viviana Cocco Mariani, and Leandro dos Santos Coelho. "Enhanced Flower Pollination Approach Applied to Electromagnetic Optimization." In International Conference on Evolutionary Computation Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0005074502230227.

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