A species-based flower pollination algorithm with increased selection pressure in abiotic local pollination and enhanced intensification


KNOWLEDGE-BASED SYSTEMS, vol.225, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 225
  • Publication Date: 2021
  • Doi Number: 10.1016/j.knosys.2021.107125
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Computer & Applied Sciences, INSPEC, Library and Information Science Abstracts, Library, Information Science & Technology Abstracts (LISTA)
  • Keywords: Flower pollination algorithm, Bio-inspired metaheuristics, Multi-population algorithms, Global optimization, OPTIMIZATION
  • Dokuz Eylül University Affiliated: Yes


Flower Pollination Algorithm (FPA) is a bio-inspired metaheuristic that simulates pollination behavior of flowers. FPA is introduced to solve global optimization problems. Subsequently, it has been applied to a variety of problems. The present study introduces some new extensions and modifications for FPA. In this respect, first, abiotic pollination mechanism of FPA is modified. Secondarily, in order to control convergence speed, a step size function that is used in both global and local pollination along with the randomness factor is adopted. Finally, FPA is extended as a species-based algorithm by partitioning whole population into smaller-sized groups that independently search for promising regions. Performances of the proposed extensions are analyzed by using the well-known unconstrained function optimization problems and Morrison and De Jong's field of cones function. Finally, non parametric statistical tests are conducted to demonstrate possible significant improvements over standard FPA. As shown by these statistically verified results, the first FPA modification with the proposed selection mechanism and step size function achieves the best results in global optimization problems while the species-based FPA modification is found as a promising algorithm to solve multi-modal problems of De Jong's field of cones function. (C) 2021 Elsevier B.V. All rights reserved.