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6 papers · 1 filter
Bat Algorithm is Better Than Intermittent Search Strategy
Xin-She Yang, Suash Deb, Simon Fong
The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm c…
Cuckoo Search: A Brief Literature Review
I. Fister, X. S. Yang, D. Fister
Cuckoo search (CS) was introduced in 2009, and it has attracted great attention due to its promising efficiency in solving many optimization problems and real-world applications. I…
Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization
Xin-She Yang, M. Karamanoglu, X. S. He
Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accuratel…
Applications and Analysis of Bio-Inspired Eagle Strategy for Engineering Optimization
Xin-She Yang, M. Karamanoglu, T. O. Ting +1
All swarm-intelligence-based optimization algorithms use some stochastic components to increase the diversity of solutions during the search process. Such randomization is often re…
Cuckoo Search: Recent Advances and Applications
Xin-She Yang, Suash Deb
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 funda…
Nature-Inspired Mateheuristic Algorithms: Success and New Challenges
Xin-She Yang
Despite the increasing popularity of metaheuristics, many crucially important questions remain unanswered. There are two important issues: theoretical framework and the gap between…