Research Area:  Metaheuristic Computing

Abstract:

In this paper, a modified flower pollination algorithm (MFPA) is proposed to improve the performance of the classical algorithm and to tackle the nonlinear equation systems widely used in engineering and science fields. In addition, the differential evolution (DE) is integrated with MFPA to strengthen its exploration operator in a new variant called HFPA. Those two algorithms were assessed using 23 well-known mathematical unimodal and multimodal test functions and 27 well-known nonlinear equation systems, and the obtained outcomes were extensively compared with those of eight well-known metaheuristic algorithms under various statistical analyses and the convergence curve. The experimental findings show that both MFPA and HFPA are competitive together and, compared to the others, they could be superior and competitive for most test cases.

Keywords:  
lower pollination algorithm
systems
nonlinear equations global optimization
differential evolution

Author(s) Name:  Mohamed Abdel-Basset, Reda Mohamed, Safaa Saber, S. S. Askar, Mohamed Abouhawwash

Publisher name:  MDPI

DOI:  10.3390/math9141661

Volume Information:  volume 9

Paper Link:   https://www.mdpi.com/2227-7390/9/14/1661