Global convergence analysis of the flower pollination algorithm: a Discrete-Time Markov Chain Approach
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1352
- Type
- E - Conference contribution
- DOI
-
10.1016/j.procs.2017.05.020
- Title of conference / published proceedings
- Procedia Computer Science, Volume 108
- First page
- 1354
- Volume
- 108
- Issue
- -
- ISSN
- 1877-0509
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2017
- URL
-
http://eprints.mdx.ac.uk/22008/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a rigorous theoretical analysis of the flower pollination algorithm (FPA), developed earlier by our research group in 2014. The FPA has been shown by various studies to be very efficient in solving nonlinear, multi-objective optimisation problems. This work is significant because for the first time the global convergence of the FPA is analysed using a discrete-time Markov chain framework. The impact of this work is visible because it has identified the correct conditions for the FPA convergence, and thus enables other researchers to use this algorithm effectively for various design applications.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
