Journal ArticleDOI
An improved fruit fly optimization algorithm for continuous function optimization problems
TLDR
In the proposed IFFO, a new control parameter is introduced to tune the search scope around its swarm location adaptively and a new solution generating method is developed to enhance accuracy and convergence rate of the algorithm.Abstract:
This paper presents an improved fruit fly optimization (IFFO) algorithm for solving continuous function optimization problems. In the proposed IFFO, a new control parameter is introduced to tune the search scope around its swarm location adaptively. A new solution generating method is developed to enhance accuracy and convergence rate of the algorithm. Extensive computational experiments and comparisons are carried out based on a set of 29 benchmark functions from the literature. The computational results show that the proposed IFFO not only significantly improves the basic fruit fly optimization algorithm but also performs much better than five state-of-the-art harmony search algorithms.read more
Citations
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Journal ArticleDOI
Evolving support vector machines using fruit fly optimization for medical data classification
TL;DR: The empirical results demonstrate that the proposed FOA-SVM method can obtain much more appropriate model parameters as well as significantly reduce the computational time, which generates a high classification accuracy.
Journal ArticleDOI
Gaussian mutational chaotic fruit fly-built optimization and feature selection
Xiang Zhang,Yueting Xu,Caiyang Yu,Ali Asghar Heidari,Ali Asghar Heidari,Shimin Li,Huiling Chen,Chengye Li +7 more
TL;DR: Numerical results show that two embedded strategies will effectively boost the performance of FOA for optimization tasks and prove that MCFOA can obtain the optimal classification accuracy.
Journal ArticleDOI
Chaotic fruit fly optimization algorithm
TL;DR: Improved standard FOA is improved by introducing the novel parameter integrated with chaos and overall research findings show that FOA with Chebyshev map show superiority in terms of reliability of global optimality and algorithm success rate.
Journal ArticleDOI
A Survey of Learning-Based Intelligent Optimization Algorithms
TL;DR: A comprehensive survey of LIOAs is conducted in this paper, which includes statistical analysis about LIOA, classification of L IOA learning method, application of LioAs in complex optimization scenarios, and L IOAs in engineering applications.
Journal ArticleDOI
An improved fruit fly optimization algorithm and its application to joint replenishment problems
Lin Wang,Yuanlong Shi,Shan Liu +2 more
TL;DR: Experimental results show that the proposed IFOA has better comprehensive performance than the original FOA, differential evolution algorithm, and particle swarm optimization algorithm and is a potential tool for various complex optimization problems.
References
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Evolutionary programming made faster
Xin Yao,Yong Liu,Guangming Lin +2 more
TL;DR: A "fast EP" (FEP) is proposed which uses a Cauchy instead of Gaussian mutation as the primary search operator and is proposed and tested empirically, showing that IFEP performs better than or as well as the better of FEP and CEP for most benchmark problems tested.
Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization
Ponnuthurai Nagaratnam Suganthan,Nikolaus Hansen,Jing Liang,Kalyanmoy Deb,Y. P. Chen,Anne Auger,Santosh Tiwari +6 more
TL;DR: This special session is devoted to the approaches, algorithms and techniques for solving real parameter single objective optimization without making use of the exact equations of the test functions.
Journal ArticleDOI
A comparative study of Artificial Bee Colony algorithm
Dervis Karaboga,Bahriye Akay +1 more
TL;DR: Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.
Journal ArticleDOI
An improved harmony search algorithm for solving optimization problems
TL;DR: The impacts of constant parameters on harmony search algorithm are discussed and a strategy for tuning these parameters is presented and the proposed algorithm can find better solutions when compared to HS and other heuristic or deterministic methods.
Journal ArticleDOI
A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice
Kang-Seok Lee,Zong Woo Geem +1 more
TL;DR: A new harmony search (HS) meta-heuristic algorithm-based approach for engineering optimization problems with continuous design variables conceptualized using the musical process of searching for a perfect state of harmony using a stochastic random search instead of a gradient search.