Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.

[1]  Mahamed G. H. Omran,et al.  Global-best harmony search , 2008, Appl. Math. Comput..

[2]  Michel Gendreau,et al.  Handbook of Metaheuristics , 2010 .

[3]  R. K. Singh,et al.  A fuzzy TOPSIS based approach for e-sourcing , 2011, Eng. Appl. Artif. Intell..

[4]  Mohamed Rehan Karim,et al.  Optimization of a Transit Services Model with a Feeder Bus and Rail System Using Metaheuristic Algorithms , 2015, J. Comput. Civ. Eng..

[5]  Francisco de A. T. de Carvalho,et al.  Kernel fuzzy c-means with automatic variable weighting , 2014, Fuzzy Sets Syst..

[6]  Mark A. Girolami,et al.  Mercer kernel-based clustering in feature space , 2002, IEEE Trans. Neural Networks.

[7]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[8]  Hong-Jie Xing,et al.  Further improvements in Feature-Weighted Fuzzy C-Means , 2014, Information Sciences.

[9]  Youwei Wang,et al.  Novel feature selection method based on harmony search for email classification , 2015, Knowl. Based Syst..

[10]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[11]  Luca Maria Gambardella,et al.  A survey on metaheuristics for stochastic combinatorial optimization , 2009, Natural Computing.

[12]  Do Guen Yoo,et al.  Approximate solving of nonlinear ordinary differential equations using least square weight function and metaheuristic algorithms , 2015, Eng. Appl. Artif. Intell..

[13]  Bilal Alatas,et al.  Chaotic harmony search algorithms , 2010, Appl. Math. Comput..

[14]  Do Guen Yoo,et al.  Application of multi‐objective evolutionary algorithms for the rehabilitation of storm sewer pipe networks , 2017 .

[15]  Ardeshir Bahreininejad,et al.  WEIGHT OPTIMIZATION OF TRUSS STRUCTURES USING WATER CYCLE ALGORITHM , 2013 .

[16]  Miin-Shen Yang,et al.  A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction , 2008, Pattern Recognit. Lett..

[17]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[18]  Wei Yang,et al.  An MAGDM based on constrained FAHP and FTOPSIS and its application to supplier selection , 2011, Math. Comput. Model..

[19]  Witold Pedrycz,et al.  Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study , 2010, Fuzzy Sets Syst..

[20]  Shitong Wang,et al.  Attribute weighted mercer kernel based fuzzy clustering algorithm for general non-spherical datasets , 2006, Soft Comput..

[21]  M. Fesanghary,et al.  An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..

[22]  Marcello Braglia,et al.  Harmony search algorithm for single-machine scheduling problem with planned maintenance , 2014, Comput. Ind. Eng..

[23]  Do Guen Yoo,et al.  Improved mine blast algorithm for optimal cost design of water distribution systems , 2015 .