Research Area:  Metaheuristic Computing

Abstract:

Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all issues related to FPA: biological inspiration, fundamentals, previous studies and comparisons, implementation, variants, hybrids, and applications. Besides, it makes a comparison between FPA and six different metaheuristics such as genetic algorithm, cuckoo search, grasshopper optimization algorithm, and others on solving a constrained engineering optimization problem . The experimental results are statistically analyzed with non-parametric Friedman test which indicates that FPA is superior more than other competitors in solving the given problem.

Keywords:  
Flower pollination algorithm
computational intelligence
biological inspiration
fundamentals
genetic algorithm
cuckoo search
grasshopper optimization

Author(s) Name:  Mohamed Abdel-Basset, Laila A. Shawky

Publisher name:  Springer

DOI:  10.1007/s10462-018-9624-4

Volume Information:  52, pages 2533–2557

Paper Link:   https://link.springer.com/article/10.1007/s10462-018-9624-4