 # 和声搜索算法

## Harmony Search Algorithm

Harmony search tries to find a vector which optimizes (minimizes or maximizes) a certain objective function.

The algorithm has the following steps:

Step 1: Generate random vectors () as many as (harmony memory size), then store them in harmony memory (HM).

Step 2: Generate a new vector . For each component ,

with probability (harmony memory considering rate; 0 ≤ ≤ 1), pick the stored value from HM:

with probability , pick a random value within the allowed range.

Step 3: Perform additional work if the value in Step 2 came from HM.

with probability (pitch adjusting rate; 0 ≤ ≤ 1), change by a small amount: or for discrete variable; or for continuous variable.

with probability , do nothing.

Step 4: If is better than the worst vector in HM, replace with .

Step 5: Repeat from Step 2 to Step 4 until termination criterion (e.g. maximum iterations) is satisfied.

The parameters of the algorithm are

= the size of the harmony memory. It generally varies from 1 to 100. (typical value = 30)

= the rate of choosing a value from the harmony memory. It generally varies from 0.7 to 0.99. (typical value = 0.9)

= the rate of choosing a neighboring value. It generally varies from 0.1 to 0.5. (typical value = 0.3)

= the amount between two neighboring values in discrete candidate set.

(fret width, formerly bandwidth) = the amount of maximum change in pitch adjustment. This can be (0.01 × allowed range) to (0.001 × allowed range).

It is possible to vary the parameter values as the search progresses, which gives an effect similar to simulated annealing.

Parameter-setting-free researches have been also performed. In the researches, algorithm users do not need tedious parameter setting process.

see more in :

http://en.wikipedia.org/wiki/Harmony_search 文件下载列表
HS.zip (1.71KB)

HS.m