A Modified Harmony Search Algorithm for Optimization Problems

Harmony search (HS) algorithm is a new meta-heuristic optimization algorithm inspired from the music improvisation process. Though the excellent performance makes it wildly used in many areas, it is easy to get trapped in local minima. This paper is to introduce a modified harmony search algorithm to improve the performance of HS algorithm. the method is implemented by adding an "innovative" process on global harmony search algorithm (GHSA), a variant of HS algorithm. This modification would be easy to make a balance of diversification and intensification. the benchmarks are designed to test the performance of the modified HS algorithm and the results show that the innovative HS algorithm has a better performance than the basic HS algorithm and its variants. in addition, to investigate the influence of parameter bw on the algorithm's performance, the tests are also conducted under the parameter bw with different types.

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

[2]  Bijaya K. Panigrahi,et al.  Exploratory Power of the Harmony Search Algorithm: Analysis and Improvements for Global Numerical Optimization , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  Zong Woo Geem,et al.  Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm , 2007, IWANN.

[4]  K. Lee,et al.  A new structural optimization method based on the harmony search algorithm , 2004 .

[5]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

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

[7]  Xiangfei Nie,et al.  Intrinsic Dimensionality Estimation with Neighborhood Convex Hull , 2007 .

[8]  Li Li,et al.  A Novel Hybrid Real-Valued Genetic Algorithm for Optimization Problems , 2007 .

[9]  Dervis Karaboga,et al.  Proportional—Integral—Derivative Controller Design by Using Artificial Bee Colony, Harmony Search, and the Bees Algorithms , 2010 .

[10]  Liang Li,et al.  The Harmony Search Algorithm in Combination with Particle Swarm Optimization and its Application in the Slope Stability Analysis , 2009, 2009 International Conference on Computational Intelligence and Security.

[11]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[12]  Woo-seok Jang,et al.  Hybrid Simplex-Harmony search method for optimization problems , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[13]  Erik Valdemar Cuevas Jiménez,et al.  Circle Detection by Harmony Search Optimization , 2012, J. Intell. Robotic Syst..

[14]  Xiao Zhi Gao,et al.  Modified Harmony Search Methods for Uni-Modal and Multi-Modal Optimization , 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

[15]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .

[16]  Li Li,et al.  A Novel Hybrid Real-Valued Genetic Algorithm for Optimization Problems , 2007, 2007 International Conference on Computational Intelligence and Security (CIS 2007).

[17]  Qun Niu,et al.  A hybrid binary harmony search algorithm inspired by ant system , 2011, 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS).

[18]  M. Fesanghary,et al.  Combined heat and power economic dispatch by harmony search algorithm , 2007 .

[19]  Jie-sheng Wang,et al.  PCNN Edge Detection of Sintering Pellets Image Based on Hybrid Harmony Search Algorithm , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[20]  Rajesh Kumar,et al.  An Intelligent Tuned Harmony Search algorithm for optimisation , 2012, Inf. Sci..

[21]  Y. M. Cheng,et al.  An improved harmony search minimization algorithm using different slip surface generation methods for slope stability analysis , 2008 .

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

[23]  Yu Wang,et al.  Self-adaptive learning based particle swarm optimization , 2011, Inf. Sci..