By Xiaolei Wang, Xiao-Zhi Gao, Kai Zenger
This short presents a close advent, dialogue and bibliographic evaluation of the nature1-inspired optimization set of rules known as concord seek. It makes use of various simulation effects to illustrate the benefits of concord seek and its variations and likewise their drawbacks. The authors express how weaknesses should be amended through hybridization with different optimization equipment. The concord seek procedure with purposes may be of worth to researchers in computational intelligence in demonstrating the cutting-edge of study on an set of rules of present curiosity. It additionally is helping researchers and practitioners of electric and desktop engineering extra quite often in acquainting themselves with this system of vector-based optimization.
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Extra info for An Introduction to Harmony Search Optimization Method
10. F10 function (Random-Peaks function) f ðx; yÞ ¼ Q X 2 2 ai efÀbi ½ðxÀxi Þ þðyÀyi Þ g ; À5 x; y 5: ð5:10Þ i¼1 Q is the number of peaks, and ðxi À yi Þ is the location of each peak. ai ; bi ; xi ; yi are given as follows: ai ¼ 1 þ 2v; ð5:11Þ bi ¼ 2 þ v; ð5:12Þ xi ¼ yi ¼ À5 þ 10v; ð5:13Þ where v is uniformly distributed within the interval [0, 1]. In our simulations, Q = 10, which means that there are ten maximal solutions to be located. Both the HS and n-HS are employed to obtain the optimal solutions to these functions, and their performances are compared with each other.
More details of the generation of x0 are illustrated in Fig. 1. Based on the principle of the DC, the distances between x0 and x1 ; x2 ; . ; xn are calculated as d1, d2, …, dn. The harmony member xi that has the minimal distance to x0 is selected. If the fitness of x0 is greater than that of xi ; the latter will be replaced by the former. Otherwise, x0 is disregarded, and the iteration procedure continues. IF f ðx0 Þ [ f ðxi Þ replace xi with x0 ELSE disregard x0 END 34 5 The Hybrid Strategies of Harmony Search… Note that the above DC-like policy only applies to the solution candidates generated from the harmony memory members.
7 Pseudo-codes of HS-OBL x. 39 Wood function: À Á2 À Á2 f ð xÞ ¼ 100 x2 À x21 þð1 À x1 Þ2 þ90 x4 À x23 h i þ ð1 À x3 Þ2 þ10:1 ðx2 À 1Þ2 þðx4 À 1Þ2 þ 19:8ðx2 À 1Þðx4 À 1Þ; ð5:24Þ x 2 ½À10; 20: It should be stressed that different from the conventional function settings, the variable ranges of these functions used here are all extended and asymmetric, which may considerably increase the difficulty of the optimization tasks. Generally, evaluation of the objective function is the most time-consuming part in a lot of practical optimization systems.