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Power law-based local search in spider monkey optimisation for lower order system modelling.
- Source :
-
International Journal of Systems Science . Jan2017, Vol. 48 Issue 1, p150-160. 11p. - Publication Year :
- 2017
-
Abstract
- The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00207721
- Volume :
- 48
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- International Journal of Systems Science
- Publication Type :
- Academic Journal
- Accession number :
- 118353438
- Full Text :
- https://doi.org/10.1080/00207721.2016.1165895