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The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this" /> <meta name="twitter:image" content="https://0.academia-photos.com/344652/1098577/1370066/s200_xin-she.yang.jpg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/33506786/Global_Convergence_Analysis_of_the_Flower_Pollination_Algorithm_A_Discrete_Time_Markov_Chain_Approach" /> <meta property="og:title" content="Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="Flower pollination algorithm is a recent metaheuristic algorithm for solving nonlinear global optimization problems. The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this" /> <meta property="article:author" content="https://cambridge.academia.edu/XinSheYang" /> <meta name="description" content="Flower pollination algorithm is a recent metaheuristic algorithm for solving nonlinear global optimization problems. The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this" /> <title>(PDF) Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach | Xin-She Yang - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/33506786/Global_Convergence_Analysis_of_the_Flower_Pollination_Algorithm_A_Discrete_Time_Markov_Chain_Approach" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '49879c2402910372f4abc62630a427bbe033d190'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732394641000); window.Aedu.timeDifference = new Date().getTime() - 1732394641000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"Flower pollination algorithm is a recent metaheuristic algorithm for solving nonlinear global optimization problems. The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this algorithm mathematically and prove its convergence properties by using Markov chain theory. By constructing the appropriate transition probability for a population of flower pollen and using the homogeneity property, it can be shown that the constructed stochastic sequences can converge to the optimal set. Under the two proper conditions for convergence, it is proved that the simplified flower pollination algorithm can indeed satisfy these convergence conditions and thus the global convergence of this algorithm can be guaranteed. Numerical experiments are used to demonstrate that the flower pollination algorithm can converge quickly in practice and can thus achieve global optimality efficiently.","author":[{"@context":"https://schema.org","@type":"Person","name":"Xin-She Yang"}],"contributor":[],"dateCreated":"2017-06-16","dateModified":"2017-06-16","datePublished":null,"headline":"Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach","inLanguage":"en","keywords":["Optimization techniques","Nature-Inspired Computing","Bio and Nature Inspired Algorithms","Nature-Inspired Algorithm","Flower Pollination 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The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this algorithm mathematically and prove its convergence properties by using Markov chain theory. By constructing the appropriate transition probability for a population of flower pollen and using the homogeneity property, it can be shown that the constructed stochastic sequences can converge to the optimal set. Under the two proper conditions for convergence, it is proved that the simplified flower pollination algorithm can indeed satisfy these convergence conditions and thus the global convergence of this algorithm can be guaranteed. Numerical experiments are used to demonstrate that the flower pollination algorithm can converge quickly in practice and can thus achieve global optimality efficiently."},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach","broadcastable":true,"draft":false,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [344652]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":53544177,"attachmentType":"pdf"}"><img alt="First page of “Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/53544177/mini_magick20190120-9125-zm8peo.png?1548035172" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="344652" href="https://cambridge.academia.edu/XinSheYang"><img alt="Profile image of Xin-She Yang" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/344652/1098577/1370066/s65_xin-she.yang.jpg" />Xin-She Yang</a></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Flower pollination algorithm is a recent metaheuristic algorithm for solving nonlinear global optimization problems. The algorithm has also been extended to solve multiobjective optimization with promising results. In this work, we analyze this algorithm mathematically and prove its convergence properties by using Markov chain theory. By constructing the appropriate transition probability for a population of flower pollen and using the homogeneity property, it can be shown that the constructed stochastic sequences can converge to the optimal set. Under the two proper conditions for convergence, it is proved that the simplified flower pollination algorithm can indeed satisfy these convergence conditions and thus the global convergence of this algorithm can be guaranteed. Numerical experiments are used to demonstrate that the flower pollination algorithm can converge quickly in practice and can thus achieve global optimality efficiently.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":53544177,"attachmentType":"pdf","workUrl":"https://www.academia.edu/33506786/Global_Convergence_Analysis_of_the_Flower_Pollination_Algorithm_A_Discrete_Time_Markov_Chain_Approach"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":53544177,"attachmentType":"pdf","workUrl":"https://www.academia.edu/33506786/Global_Convergence_Analysis_of_the_Flower_Pollination_Algorithm_A_Discrete_Time_Markov_Chain_Approach"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="53544177" data-landing_url="https://www.academia.edu/33506786/Global_Convergence_Analysis_of_the_Flower_Pollination_Algorithm_A_Discrete_Time_Markov_Chain_Approach" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="2208928" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/2208928/Flower_Pollination_Algorithm_for_Global_Optimization">Flower Pollination Algorithm for Global Optimization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="344652" href="https://cambridge.academia.edu/XinSheYang">Xin-She Yang</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Unconventional Computation and Natural Computation, 2012</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Flower Pollination Algorithm for Global Optimization","attachmentId":32596976,"attachmentType":"pdf","work_url":"https://www.academia.edu/2208928/Flower_Pollination_Algorithm_for_Global_Optimization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/2208928/Flower_Pollination_Algorithm_for_Global_Optimization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="24232367" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/24232367/A_Modified_Flower_Pollination_Algorithm_for_Global_Optimization">A Modified Flower Pollination Algorithm for Global Optimization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="16622758" href="https://cairo.academia.edu/EmadNabil">Emad Nabil</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Expert and intelligent systems try to simulate intelligent human experts in solving complex real-world problems. The domain of problems varies from engineering and industry to medicine and education. In most situations, the system is required to take decisions based on multiple inputs, but the search space is usually very huge so that it will be very hard to use the traditional algorithms to take a decision; at this point, the metaheuristic algorithms can be used as an alternative tool to find near-optimal solutions. Thus, inventing new metaheuristic techniques and enhancing the current algorithms is necessary. In this paper, we introduced an enhanced variant of the Flower Pollination Algorithm (FPA). We hybridized the standard FPA with the Clonal Selection Algorithm (CSA) and tested the new algorithm by applying it to 23 optimization benchmark problems. The proposed algorithm is compared with five famous optimization algorithms, namely, Simulated Annealing, Genetic Algorithm, Flower Pollination Algorithm, Bat Algorithm, and Firefly Algorithm. The results show that the proposed algorithm is able to find more accurate solutions than the standard FPA and the other four techniques. The superiority of the proposed algorithm nominates it for being a part of intelligent and expert systems.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Modified Flower Pollination Algorithm for Global Optimization","attachmentId":44564125,"attachmentType":"pdf","work_url":"https://www.academia.edu/24232367/A_Modified_Flower_Pollination_Algorithm_for_Global_Optimization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/24232367/A_Modified_Flower_Pollination_Algorithm_for_Global_Optimization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="77708259" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/77708259/Dynamic_Probability_Selection_for_Flower_Pollination_Algorithm_Based_on_Metropolishastings_Criteria">Dynamic Probability Selection for Flower Pollination Algorithm Based on Metropolishastings Criteria</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9741682" href="https://usm.academia.edu/AbdullahNasser">Abdullah B. Nasser</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2020</p><p class="ds-related-work--abstract ds2-5-body-sm">Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimisation function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. Adopting the problem of t-way test suite generation as the case study and with the comparative evaluation with the original FPA, FPA-MH gave promising results owing to its dynamic and adaptive se...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Dynamic Probability Selection for Flower Pollination Algorithm Based on Metropolishastings Criteria","attachmentId":85005006,"attachmentType":"pdf","work_url":"https://www.academia.edu/77708259/Dynamic_Probability_Selection_for_Flower_Pollination_Algorithm_Based_on_Metropolishastings_Criteria","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/77708259/Dynamic_Probability_Selection_for_Flower_Pollination_Algorithm_Based_on_Metropolishastings_Criteria"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="42682955" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/42682955/Flower_Pollination_Algorithm_An_Introduction">Flower Pollination Algorithm: An Introduction</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="344652" href="https://cambridge.academia.edu/XinSheYang">Xin-She Yang</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2014</p><p class="ds-related-work--abstract ds2-5-body-sm">This presentation explains the fundamental ideas of the standard Flower Pollination Algorithm (FPA), which also contains the links to the free Matlab codes at Mathswork file exchanges and the animations of numerical simulations (video at Youtube). An example of multi-objective flower pollination algorithm (MOPFA) is also given with link to the Matlab code.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Flower Pollination Algorithm: An Introduction","attachmentId":62899444,"attachmentType":"pdf","work_url":"https://www.academia.edu/42682955/Flower_Pollination_Algorithm_An_Introduction","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/42682955/Flower_Pollination_Algorithm_An_Introduction"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="35039342" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/35039342/Variants_of_the_Flower_Pollination_Algorithm_A_Review">Variants of the Flower Pollination Algorithm: A Review</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1022261" href="https://uokufa.academia.edu/ZaidAlyasseri">Zaid Alyasseri</a></div><p class="ds-related-work--abstract ds2-5-body-sm">The flower pollination algorithm (FPA) is a nature-inspired algorithm that imitates the pollination behavior of flowering plants. Optimal plant reproduction strategy involves the survival of the fittest as well as the optimal reproduction of plants in terms of numbers. These factors represent the fundamentals of the FPA and are optimization-oriented. Yang developed the FPA in 2012, which has since shown superiority to other metaheuristic algorithms in solving various real-world problems, such as power and energy, signal and image processing, communications , structural design, clustering and feature selection, global function optimization , computer gaming, and wireless sensor networking. Recently, many variants of FPA have been developed by modification, hybridization, and parameter-tuning to cope with the complex nature of optimization problems. Therefore, this chapter provides a comprehensive review for FPA variants from 2012 to present.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Variants of the Flower Pollination Algorithm: A Review","attachmentId":54901435,"attachmentType":"pdf","work_url":"https://www.academia.edu/35039342/Variants_of_the_Flower_Pollination_Algorithm_A_Review","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/35039342/Variants_of_the_Flower_Pollination_Algorithm_A_Review"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="19974519" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/19974519/A_Review_of_the_Applications_of_Bio_Inspired_Flower_Pollination_Algorithm">A Review of the Applications of Bio-Inspired Flower Pollination Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32123152" href="https://malaya.academia.edu/ChiromaHaruna">Chiroma Haruna</a></div><p class="ds-related-work--abstract ds2-5-body-sm">The Flower Pollination Algorithm (FPA) is a novel bio-inspired optimization algorithm that mimics the real life processes of the flower pollination. In this paper, we review the applications of the Single Flower Pollination Algorithm (SFPA), Multi-objective Flower Pollination Algorithm an extension of the SFPA and the Hybrid of FPA with other bio-inspired algorithms. The review has shown that there is still a room for the extension of the FPA to Binary FPA. The review presented in this paper can inspire researchers in the bio-inspired algorithms research community to further improve the effectiveness of the PFA as well as to apply the algorithm in other domains for solving real life, complex and nonlinear optimization problems in engineering and industry. Further research and open questions were highlighted in the paper.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Review of the Applications of Bio-Inspired Flower Pollination Algorithm","attachmentId":40940217,"attachmentType":"pdf","work_url":"https://www.academia.edu/19974519/A_Review_of_the_Applications_of_Bio_Inspired_Flower_Pollination_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/19974519/A_Review_of_the_Applications_of_Bio_Inspired_Flower_Pollination_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="62877239" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/62877239/Recent_Advances_in_Flower_Pollination_Algorithm">Recent Advances in Flower Pollination Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="140393508" href="https://neu.academia.edu/NabilDiab">Nabil Diab</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Computer Applications Technology and Research, 2016</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Recent Advances in Flower Pollination Algorithm","attachmentId":75501466,"attachmentType":"pdf","work_url":"https://www.academia.edu/62877239/Recent_Advances_in_Flower_Pollination_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/62877239/Recent_Advances_in_Flower_Pollination_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="91439133" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91439133/Flower_pollination_algorithm_development_a_state_of_art_review">Flower pollination algorithm development: a state of art review</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="180438277" href="https://independent.academia.edu/sangeetapant1">sangeeta pant</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of System Assurance Engineering and Management, 2017</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Flower pollination algorithm development: a state of art review","attachmentId":94726952,"attachmentType":"pdf","work_url":"https://www.academia.edu/91439133/Flower_pollination_algorithm_development_a_state_of_art_review","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91439133/Flower_pollination_algorithm_development_a_state_of_art_review"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="35577745" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/35577745/Flower_Pollination_Algorithm_for_Multimodal_Optimization">Flower Pollination Algorithm for Multimodal Optimization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="17675683" href="https://guadalajara.academia.edu/JorgeG%C3%A1lvez">Jorge Gálvez</a></div><p class="ds-related-work--abstract ds2-5-body-sm">This paper proposes a new algorithm called Multimodal Flower Pollination Algorithm (MFPA). Under MFPA, the original Flower Pollination Algorithm (FPA) is enhanced with multimodal capabilities in order to find all possible optima in an optimization problem. The performance of the proposed MFPA is compared to several multimodal approaches considering the evaluation in a set of well-known benchmark functions. Experimental data indicate that the proposed MFPA provides better results over other multimodal competitors in terms of accuracy and robustness.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Flower Pollination Algorithm for Multimodal Optimization","attachmentId":55443799,"attachmentType":"pdf","work_url":"https://www.academia.edu/35577745/Flower_Pollination_Algorithm_for_Multimodal_Optimization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/35577745/Flower_Pollination_Algorithm_for_Multimodal_Optimization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="8838601" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/8838601/A_Comparative_Study_of_Flower_Pollination_Algorithm_and_Bat_Algorithm_on_Continuous_Optimization_Problems">A Comparative Study of Flower Pollination Algorithm and Bat Algorithm on Continuous Optimization Problems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="19251215" href="https://aust.academia.edu/NazmusSakibRupol">Nazmus Sakib Rupol</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Nature is a rich source of inspiration, which has inspired many researchers in many ways. Nowadays, new algorithms have been developed by the inspiration from nature. The flower pollination algorithm is based on the characteristics of pollination process of flowers plants. Pollination is a natural biological process of mating in plants. In flowers, pollen is carried to stigma through some mechanisms that confirm a proper balance in the genetic creations of the species. Another nature inspired algorithm — the Bat algorithm is based on the echolocation behavior of bats. In this paper, the Flower pollination algorithm is compared with the basic Bat algorithm. We have tested these two algorithms on both unimodal and multimodal, low and high dimensional continuous functions. Simulation results suggest that the Flower pollination algorithm can perform much better than the Bat algorithm on the continuous optimization problems.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Comparative Study of Flower Pollination Algorithm and Bat Algorithm on Continuous Optimization Problems","attachmentId":35179086,"attachmentType":"pdf","work_url":"https://www.academia.edu/8838601/A_Comparative_Study_of_Flower_Pollination_Algorithm_and_Bat_Algorithm_on_Continuous_Optimization_Problems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/8838601/A_Comparative_Study_of_Flower_Pollination_Algorithm_and_Bat_Algorithm_on_Continuous_Optimization_Problems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":53544177,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":53544177,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_53544177" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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