Hybridising harmony search with a Markov blanket for gene selection problems

Tournament-based harmony search algorithm for non-convex economic load dispatch problem

“…The HS, which is the recent evolutionary algorithm proposed in [40], is considered to be an efficient approximation technique due to its derivative-free characteristics [53]. Literatures have shown the usability of HS algorithm have been increasing over the year to address a wide range of optimization problems [76,12,39,37,38,46]. Similarly, the HS algorithm has been modified and hybridized with other efficient methods to cope with the combinatorial nature of highly constrained optimization problems [4,7,1,10,11,14].…”

Fast control optimization for switched linear systems based on harmony search algorithm

“…HS algorithm mimics the musician's improvisation process to find a global optimal solution or a near optimal solution determined by an objective via searching experience and effective exploration. Due to its simplicity, generality and flexibility and its lower parameter sensitivity [32,33], HS algorithm has been successfully applied to various types of non-linear optimization engineering problems including reliability problems [34,35], energy system dispatch [36] and the design of the fuzzy controller [37][38][39]. Other applications of HS algorithm can be found in [40].…”

A novel aggregate gene selection method for microarray data classification

“…Likewise, a general framework of sample weighting to improve the stability of feature selection method under sample variations was presented in [25]. A hybrid approach that embeds the Markov Blanket with the harmony search algorithm for gene selection was suggested by Shreem et al [19]. The procedure works well on selected genes with higher correlation coefficients based on symmetrical uncertainty.…”