Hybrid Differential Evolution Harmony Search Algorithm for Power Economic Dispatch Problems

2013 ◽  
Vol 415 ◽  
pp. 345-348
Author(s):  
Hong Gang Xia ◽  
Qing Zhou Wang

In this paper, a hybrid differential evolution harmony search (HDEHS) algorithm was presented for solving power economic dispatch problems. In this algorithm, mutation and crossover operation instead of harmony memory consideration and pitch adjustment operation, this improved the algorithm convergence rate. Moreover, dynamically adjust the key parameter (e.g. mutagenic factor F, crossover rate CR) to balance the local and global search. Based on a 13 units power system experiment simulations, the HDEHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its three improved algorithms (IHS, GHS and NGHS) that reported in recent literature.

2014 ◽  
Vol 587-589 ◽  
pp. 2295-2298
Author(s):  
Ping Zhang ◽  
Mei Ling Li ◽  
Qian Han ◽  
Yi Ning Zhang ◽  
Guo Jun Li

To intend to improve the optimization performance of harmony search (HS) algorithm, an improved global harmony search (IGHS) algorithm was presented in this paper. In this algorithm, inspired by swarm intelligence, the global best harmony are borrowed to enhance the optimization accuracy of HS; and mutation and crossover operation instead of pitch adjustment operation to improved the algorithm convergence rate. The key parameters are adjusted to balance the local and global search. Several benchmark experiment simulations, the IGHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its other three improved algorithms (IHS, GHS and SGHS) that reported in recent literature.


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