Strategies to Improve Cuckoo Search Toward Adapting Randomly Changing Environment View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-06-24

AUTHORS

Yuta Umenai , Fumito Uwano , Hiroyuki Sato , Keiki Takadama

ABSTRACT

Cuckoo Search (CS) is the powerful optimization algorithm and has been researched recently. Cuckoo Search for Dynamic Environment (D-CS) has proposed and tested in dynamic environment with multi-modality and cyclically before. It was clear that has the hold capability and can find the optimal solutions in this environment. Although these experiments only provide the valuable results in this environment, D-CS not fully explored in dynamic environment with other dynamism. We investigate and discuss the find and hold capabilities of D-CS on dynamic environment with randomness. We employed the multi-modal dynamic function with randomness and applied D-CS into this environment. We compared D-CS with CS in terms of getting the better fitness. The experimental result shows the D-CS has the good hold capability on dynamic environment with randomness. Introducing the Local Solution Comparison strategy and Concurrent Solution Generating strategy help to get the hold and find capabilities on dynamic environment with randomness. More... »

PAGES

573-582

Book

TITLE

Advances in Swarm Intelligence

ISBN

978-3-319-61823-4
978-3-319-61824-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-61824-1_62

DOI

http://dx.doi.org/10.1007/978-3-319-61824-1_62

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090239847


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