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- Publisher
- Springer Journals
- Copyright
- Copyright © 2017 by Springer Science+Business Media B.V.
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); Computer Science, general
- ISSN
- 0269-2821
- eISSN
- 1573-7462
- DOI
- 10.1007/s10462-017-9580-4
- Publisher site
- See Article on Publisher Site
Abstract
Artif Intell Rev DOI 10.1007/s10462-017-9580-4 Review of modified and hybrid flower pollination algorithms for solving optimization problems 1 1 Dhabitah Lazim · Azlan Mohd Zain · 1 2 Mahadi Bahari · Abdullah Hisham Omar © Springer Science+Business Media B.V. 2017 Abstract Flower pollination algorithm (FPA) is a nature-inspired meta-heuristics to handle a large scale optimization process. This paper reviews the previous studies on the application of FPA, modified FPA and hybrid FPA for solving optimization problems. The effectiveness of FPA for solving the optimization problems are highlighted and discussed. The improve- ment aspects include local and global search strategies and the quality of the solutions. The measured enhancements in FPA are based on various research domains. The results of review indicate the capability of the enhanced and hybrid FPA for solving optimization problems in variety of applications and outperformed the results of other established optimization techniques. Keywords Flower pollination algorithm · Optimization · Modification · Hybridization · Application · Comparison · Review 1 Introduction Optimization problems are the problems in finding the best solution from among the set of all feasible solutions. Multi-objective optimization is a common problem which involves more than one objective to be optimized synchronously. Optimization
Journal
Artificial Intelligence Review – Springer Journals
Published: Oct 14, 2017