@inproceedings{f6fcf1fbb35747f59c521687ee109210,
title = "Strategies to improve cuckoo search toward adapting randomly changing environment",
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.",
keywords = "Cuckoo Search, Dynamic environment, Swarm intelligence",
author = "Yuta Umenai and Fumito Uwano and Hiroyuki Sato and Keiki Takadama",
year = "2017",
doi = "10.1007/978-3-319-61824-1_62",
language = "English",
isbn = "9783319618234",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "573--582",
editor = "Ying Tan and Hideyuki Takagi and Yuhui Shi",
booktitle = "Advances in Swarm Intelligence - 8th International Conference, ICSI 2017, Proceedings",
note = "8th International Conference on Swarm Intelligence, ICSI 2017 ; Conference date: 27-07-2017 Through 01-08-2017",
}