A New K means Grey Wolf Algorithm for Engineering Problems

Purpose: This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves. Design/methodology/approach: The development of meta-heuristic algorithms has increased by researchers to use them extensively in the field of business, science, and engineering. In this paper, the K-means clustering algorithm is used to enhance the performance of the original GWO; the new algorithm is called K-means clustering gray wolf optimization (KMGWO). Findings: Results illustrate the efficiency of KMGWO against the GWO. To evaluate the performance of the KMGWO, KMGWO was applied to solve CEC2019 benchmark test functions.

[1]  Jorge Daniel Mello-Román,et al.  KPLS Optimization With Nature-Inspired Metaheuristic Algorithms , 2020, IEEE Access.

[2]  Xin-She Yang.  Harmony Search as a Metaheuristic Algorithm , 2009 .

[3]  A. N. Jadhav,et al.  WGC: Hybridization of exponential grey wolf optimizer with whale optimization for data clustering , 2017, Alexandria Engineering Journal.

[4]  Chnoor M. Rahman,et al.  A new evolutionary algorithm: Learner performance based behavior algorithm , 2020, Egyptian Informatics Journal.

[5]  Pavel Y. Tabakov,et al.  Design optimization of anisotropic pressure vessels with manufacturing uncertainties accounted for , 2013 .

[6]  Shaolong Sun,et al.  A novel hybrid decomposition-ensemble model based on VMD and HGWO for container throughput forecasting , 2018 .

[7]  Yongquan Zhou,et al.  Complex-valued encoding metaheuristic optimization algorithm: A comprehensive survey , 2020, Neurocomputing.

[8]  Qian Zhang,et al.  Multi-strategy boosted mutative whale-inspired optimization approaches , 2019, Applied Mathematical Modelling.

[9]  Clara Pizzuti,et al.  A K-means Based Genetic Algorithm for Data Clustering , 2016, SOCO-CISIS-ICEUTE.

[10]  Xin-She Yang,et al.  Color Image Segmentation By Cuckoo Search , 2015, Intell. Autom. Soft Comput..

[11]  H.P. Ng,et al.  Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm , 2006, 2006 IEEE Southwest Symposium on Image Analysis and Interpretation.

[12]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[13]  Xin-She Yang,et al.  Optimal test sequence generation using firefly algorithm , 2013, Swarm Evol. Comput..

[14]  Mohamed A. Tawhid,et al.  A hybridization of grey wolf optimizer and differential evolution for solving nonlinear systems , 2020, Evol. Syst..

[15]  Oscar Castillo,et al.  A New Hybridization Approach between the Fireworks Algorithm and Grey Wolf Optimizer Algorithm , 2018 .

[16]  Milan Tuba,et al.  Brain Image Segmentation Based on Firefly Algorithm Combined with K-means Clustering , 2019, Studies in Informatics and Control.

[17]  Seyed Mohammad Mirjalili,et al.  Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm , 2015, Knowl. Based Syst..

[18]  Jianjun Jiao,et al.  Inspired grey wolf optimizer for solving large-scale function optimization problems , 2018, Applied Mathematical Modelling.

[19]  Umi Kalthum Ngah,et al.  Adaptive fuzzy moving K-means clustering algorithm for image segmentation , 2009, IEEE Transactions on Consumer Electronics.

[20]  Jaza Mahmood Abdullah,et al.  Fitness Dependent Optimizer: Inspired by the Bee Swarming Reproductive Process , 2019, IEEE Access.

[21]  Mohamed A. Eid,et al.  Structural optimization of concrete arch bridges using Genetic Algorithms , 2019, Ain Shams Engineering Journal.

[22]  Hossam Faris,et al.  Grey wolf optimizer: a review of recent variants and applications , 2017, Neural Computing and Applications.

[23]  A. Ahmadyfard,et al.  Combining PSO and k-means to enhance data clustering , 2008, 2008 International Symposium on Telecommunications.

[24]  Wang Min,et al.  Improved K-means clustering based on genetic algorithm , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

[25]  Xin-She Yang,et al.  Sizing optimization of truss structures using flower pollination algorithm , 2015, Appl. Soft Comput..

[26]  Tarik A. Rashid,et al.  A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm , 2019, Comput. Intell. Neurosci..

[27]  Leandro dos Santos Coelho,et al.  Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization , 2016, Expert Syst. Appl..

[28]  Muhammad Sharif,et al.  A Survey on Medical Image Segmentation , 2015 .

[29]  Juan Zhao,et al.  An Improved Grey Wolf Optimization Algorithm with Variable Weights , 2019, Comput. Intell. Neurosci..

[30]  Xin Ma,et al.  Hybrid extreme learning machine with meta-heuristic algorithms for monthly pan evaporation prediction , 2020, Comput. Electron. Agric..

[31]  Xin-She Yang,et al.  Nature-Inspired Optimization Algorithms in Engineering: Overview and Applications , 2016, Nature-Inspired Computation in Engineering.

[32]  Fabrizio Maria Maggi,et al.  Genetic algorithms for hyperparameter optimization in predictive business process monitoring , 2018, Inf. Syst..

[33]  Chris H. Q. Ding,et al.  K-means clustering via principal component analysis , 2004, ICML.

[34]  Provas Kumar Roy,et al.  Oppositional based grey wolf optimization algorithm for economic dispatch problem of power system , 2017, Ain Shams Engineering Journal.

[35]  Yongquan Zhou,et al.  A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem , 2013, J. Appl. Math..

[36]  Marco Dorigo.  Ant colony optimization , 2004, Scholarpedia.

[37]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[38]  Pritesh Vora,et al.  A Survey on K-mean Clustering and Particle Swarm Optimization , 2013 .

[39]  Zain Anwar Ali,et al.  Path planning of multiple UAVs using MMACO and DE algorithm in dynamic environment , 2020, Measurement and Control.

[40]  Gagandeep Kaur,et al.  A Survey on Medical Image Segmentation , 2017 .

[41]  Almoataz Y. Abdelaziz,et al.  Whale optimization algorithm to tune PID and PIDA controllers on AVR system , 2019 .

[42]  Farzin Modarres Khiyabani,et al.  A whale optimization algorithm (WOA) approach for clustering , 2018 .

[43]  Tarik A. Rashid,et al.  Cat Swarm Optimization Algorithm: A Survey and Performance Evaluation , 2020, Computational intelligence and neuroscience.

[44]  Manuel Laguna,et al.  Tabu Search , 1997 .

[45]  R. Devika,et al.  Survey on clustering techniques in Twitter data , 2018, 2018 Second International Conference on Computing Methodologies and Communication (ICCMC).

[46]  Saeed Jalili,et al.  Single-pass and linear-time k-means clustering based on MapReduce , 2016, Inf. Syst..

[47]  Philipp Limbourg,et al.  Preventive maintenance scheduling by variable dimension evolutionary algorithms , 2006 .

[48]  Xin-She Yang,et al.  Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan , 2014, Appl. Soft Comput..

[49]  Md Zahidul Islam,et al.  Combining K-Means and a genetic algorithm through a novel arrangement of genetic operators for high quality clustering , 2018, Expert Syst. Appl..

[50]  Dervis Karaboga,et al.  A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..

[51]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[52]  Tarik A. Rashid,et al.  A multi hidden recurrent neural network with a modified grey wolf optimizer , 2019, PloS one.

[53]  K. Shanti Swarup,et al.  Particle swarm optimization based K-means clustering approach for security assessment in power systems , 2011, Expert Syst. Appl..

[54]  Rajesh Kumar,et al.  Intelligent Grey Wolf Optimizer - Development and application for strategic bidding in uniform price spot energy market , 2018, Appl. Soft Comput..

[55]  Urvinder Singh,et al.  Modified Grey Wolf Optimizer for Global Engineering Optimization , 2016, Appl. Comput. Intell. Soft Comput..

[56]  Hardi Mohammed,et al.  A novel hybrid GWO with WOA for global numerical optimization and solving pressure vessel design , 2020, Neural Computing and Applications.

[57]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[58]  Bijaya K. Panigrahi,et al.  Binary Grey Wolf Optimizer for large scale unit commitment problem , 2018, Swarm Evol. Comput..

[59]  Xin-She Yang,et al.  Engineering optimisation by cuckoo search , 2010, Int. J. Math. Model. Numer. Optimisation.

[60]  Chinmay Chakraborty,et al.  Chronic Wound Image Analysis by Particle Swarm Optimization Technique for Tele-Wound Network , 2017, Wirel. Pers. Commun..

[61]  Nadjet Kamel,et al.  A Sampling-PSO-K-means Algorithm for Document Clustering , 2013, ICGEC.

[62]  N. Harnpornchai,et al.  Determination of point of maximum likelihood in failure domain using genetic algorithms , 2006 .

[63]  Tom V. Mathew.  Genetic Algorithm , 2022 .

[64]  Narottam Jangir,et al.  Whale Optimization Algorithm for Constrained Economic Load Dispatch Problems—A Cost Optimization , 2018 .

[65]  Siyi Chen,et al.  Improved Alpha-Guided Grey Wolf Optimizer , 2019, IEEE Access.

[66]  Laith Mohammad Abualigah,et al.  A new feature selection method to improve the document clustering using particle swarm optimization algorithm , 2017, J. Comput. Sci..

[67]  Haiyang Li,et al.  Dynamic particle swarm optimization and K-means clustering algorithm for image segmentation , 2015 .

[68]  Sankalap Arora,et al.  Chaotic grey wolf optimization algorithm for constrained optimization problems , 2018, J. Comput. Des. Eng..

[69]  P. Sasikumar,et al.  K-Means Clustering in Wireless Sensor Networks , 2012, 2012 Fourth International Conference on Computational Intelligence and Communication Networks.

[70]  Peter Rossmanith,et al.  Simulated Annealing , 2008, Taschenbuch der Algorithmen.

[71]  Andrew Lewis,et al.  The Whale Optimization Algorithm , 2016, Adv. Eng. Softw..

[72]  Z. Ali,et al.  Cooperative Path Planning of Multiple UAVs by using Max–Min Ant Colony Optimization along with Cauchy Mutant Operator , 2020 .

[73]  Fehmi Burcin Ozsoydan,et al.  Effects of dominant wolves in grey wolf optimization algorithm , 2019, Appl. Soft Comput..

[74]  Xin-She Yang,et al.  Bat algorithm: a novel approach for global engineering optimization , 2012, 1211.6663.

[75]  Nikos A. Vlassis,et al.  The global k-means clustering algorithm , 2003, Pattern Recognit..

[76]  Siti Zaiton Mohd Hashim,et al.  Modified K-means Combined with Artificial Bee Colony Algorithm and Differential Evolution for Color Image Segmentation , 2014, INNS-CIIS.

[77]  Tarik A. Rashid,et al.  Donkey and Smuggler Optimization Algorithm: A Collaborative Working Approach to Path Finding , 2019, J. Comput. Des. Eng..

[78]  Xin-She Yang,et al.  Bat algorithm for multi-objective optimisation , 2011, Int. J. Bio Inspired Comput..

[79]  Andrew Y. Ng,et al.  Learning Feature Representations with K-Means , 2012, Neural Networks: Tricks of the Trade.

[80]  Jie-Sheng Wang,et al.  An Improved Grey Wolf Optimizer Based on Differential Evolution and Elimination Mechanism , 2019, Scientific Reports.