Cuckoo Search: Recent Advances and Applications

Abstract

Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and CS is efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as well as its applications. We analyze the algorithm and gain insight into its search mechanisms and find out why it is efficient. We also discuss the essence of algorithms and its link to self-organizing systems, and finally we propose some important topics for further research.

9 pages

References in corpus (1)

• Levy Flights, Non-local Search and Simulated Annealing

Cited by in corpus (12)

• Bat Algorithm: Literature Review and Applications
• Nature-Inspired Optimization Algorithms: Challenges and Open Problems
• Nature-Inspired Algorithms for Wireless Sensor Networks: A Comprehensive Survey
• Achievement of Minimized Combinatorial Test Suite for Configuration-Aware Software Functional Testing Using the Cuckoo Search Algorithm
• Multi-Species Cuckoo Search Algorithm for Global Optimization
• Cuckoo Search: State-of-the-Art and Opportunities
• Optimizing Readability Using Genetic Algorithms
• A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems
• RIS-Assisted D2D Communication in the Presence of Interference: Outage Performance Analysis and DNN-Based Prediction
• Social Algorithms
• hidden markov random fields and cuckoo search method for medical image segmentation
• Adjoint-based Gradient Estimation Using the Space-time Solutions of Unknown Conservation Law Simulations