Enhancing Optimization Efficiency: The Modified Flower Pollination Algorithm with Spiral Renewal Mechanism

Hussein, Nazar Khalaf; N. Sahi, Shifaa

doi:10.33899/csmj.2023.142143.1078

	Enhancing Optimization Efficiency: The Modified Flower Pollination Algorithm with Spiral Renewal Mechanism
AL-Rafidain Journal of Computer Sciences and Mathematics
Volume 17, Issue 2, December 2023, Pages 151-161 PDF (1.08 M)
Document Type: Research Paper
DOI: 10.33899/csmj.2023.142143.1078
Authors
Nazar Khalaf Hussein^* ¹; Shifaa N. Sahi²
¹College of Computer science and mathematics- University of Tikrit
²Dept. of Mathematics, College of Computer Science and Mathematics, Tikrit University, Iraq
Abstract
The Flower Pollination Algorithm (FPA) is a widely recognized swarm intelligence technique for optimization problems. However, FPA shares limitations with other swarm-based algorithms, such as susceptibility to local optima and slow convergence in high-dimensional global optimization problems. To address these challenges, the Modified Flower Pollination Algorithm (MFPA) has been proposed. By employing a balanced exploitation and exploration approach, MFPA seeks to improve exploitation capabilities and solution accuracy. In order to avoid local optima, it uses the spiral renewal mechanism from the Moth Flame Optimization (MFO) algorithm. These tactics work best together, enhancing the performance of FPA. Benchmark test functions, including those from the CEC 2017 test suite, were evaluated experimentally. The findings of comparing the performance of MFPA to other swarm intelligence algorithms and sophisticated methodologies were quite positive and encouraging.
Keywords
modified flower pollination algorithm,,; ,،optimization problems,,; ,،swarm intelligence,,; ,،spiral renewal mechanism,,; ,،benchmark test functions

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