Modified Flower Pollination Algorithm for Global Optimization

Mohamed Abdel-Basset, Reda Mohamed, Safaa Saber, S. S. Askar and Mohamed Abouhawwash
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Mohamed Abdel-Basset: Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt
Reda Mohamed: Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt
Safaa Saber: Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Zagazig 44519, Egypt
S. S. Askar: Department of Statistics and Operations Research, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Mohamed Abouhawwash: Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt

Mathematics, 2021, vol. 9, issue 14, 1-37

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: flower pollination algorithm; systems of nonlinear equations; global optimization; differential evolution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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