Linkage artificial bee colony for solving linkage problems

A novel optimization method.Evaluate using Pott model problems and linkage functions.Outperform the current methods. Nature-inspired meta-heuristics have gained popularity for the solution of many real world complex problems, and the artificial bee colony algorithm is one of the most powerful optimisation methods among the meta-heuristics. However, a major drawback prevents the artificial bee colony algorithm from accurately and efficiently finding final solutions for complex problems, whose variables interact with each other. We propose a novel optimization method based on the artificial bee colony algorithm and statistics. The proposed optimization method is evaluated for Pott models and optimization linkage functions, and the proposed method is verified to outperform traditional artificial bee colony and other meta-heuristics for those cases.

[1]  Martin Pelikan,et al.  An introduction and survey of estimation of distribution algorithms , 2011, Swarm Evol. Comput..

[2]  Kalyanmoy Deb,et al.  Real-coded Genetic Algorithms with Simulated Binary Crossover: Studies on Multimodal and Multiobjective Problems , 1995, Complex Syst..

[3]  Marjan Mernik,et al.  Is a comparison of results meaningful from the inexact replications of computational experiments? , 2016, Soft Comput..

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[6]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[7]  Junjie Li,et al.  Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions , 2011, Inf. Sci..

[8]  Milan Tuba,et al.  Different approaches in parallelization of the artificial bee colony algorithm , 2011 .

[9]  Bahriye Akay,et al.  Synchronous and asynchronous Pareto-based multi-objective Artificial Bee Colony algorithms , 2012, Journal of Global Optimization.

[10]  Dervis Karaboga,et al.  The Artificial Bee Colony algorithm in layer optimization for the maximum fundamental frequency of symmetrical laminated composite plates , 2014 .

[11]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[12]  Yeung Sam Hung,et al.  Order Statistics Correlation Coefficient as a Novel Association Measurement With Applications to Biosignal Analysis , 2007, IEEE Transactions on Signal Processing.

[13]  Dervis Karaboga,et al.  Solving Integer Programming Problems by Using Artificial Bee Colony Algorithm , 2009, AI*IA.

[14]  Francisco Herrera,et al.  Analyzing convergence performance of evolutionary algorithms: A statistical approach , 2014, Inf. Sci..

[15]  Jeng-Shyang Pan,et al.  Enhanced Artificial Bee Colony Optimization , 2022 .

[16]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[17]  Yunlong Zhu,et al.  A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm , 2010 .

[18]  D. Ackley.  A connectionist machine for genetic hillclimbing , 1987 .

[19]  S. Picek,et al.  On the efficiency of crossover operators in genetic algorithms with binary representation , 2010 .

[20]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[21]  Harikrishna Narasimhan,et al.  Parallel artificial bee colony (PABC) algorithm , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[22]  Sadan Kulturel-Konak,et al.  A review of clonal selection algorithm and its applications , 2011, Artificial Intelligence Review.

[23]  Milan Tuba,et al.  Parallelization of the artificial bee colony (ABC) algorithm , 2010 .

[24]  Marjan Mernik,et al.  A chess rating system for evolutionary algorithms: A new method for the comparison and ranking of evolutionary algorithms , 2014, Inf. Sci..

[25]  Tugrul Cavdar,et al.  A New Heuristic Approach for Inverse Kinematics of Robot Arms , 2013 .