Cuckoo search for business optimization applications

Yang, Xin-She ORCID logoORCID: https://orcid.org/0000-0001-8231-5556, Deb, Suash, Karamanoglu, Mehmet ORCID logoORCID: https://orcid.org/0000-0002-5049-2993 and He, Xingshi (2012) Cuckoo search for business optimization applications. 2012 NATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION SYSTEMS. In: National Conference on Computing and Communication Systems (NCCCS), 21 - 22 November 2012, Durgapur, West Bengal, India. . [Conference or Workshop Item] (doi:10.1109/NCCCS.2012.6412973)

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Abstract

Cuckoo search has become a popular and powerful metaheuristic algorithm for global optimization. In business optimization and applications, many studies have focused on support vector machine and neural networks. In this paper, we use cuckoo search to carry out optimization tasks and compare the performance of cuckoo search with support vector machine. By testing benchmarks such as project scheduling and bankruptcy predictions, we conclude that cuckoo search can perform better than support vector machine.

Item Type: Conference or Workshop Item (Paper)
Keywords (uncontrolled): Algorithm design and analysis; Business; Optimization; Particle swarm optimization; Prediction algorithms; Search problems; Support vector machines; algorithm; cuckoo search;metaheuristics;optimization;swarm intelligence
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 10152
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Depositing User: Mehmet Karamanoglu
Date Deposited: 25 Mar 2013 06:20
Last Modified: 16 Jun 2022 18:59
URI: https://eprints.mdx.ac.uk/id/eprint/10152

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