The function of terminating the genetic algorithm
terminate(tercrit, maxiter, objective, t, genfits,
fitvals, objval, optdif, rmcnt, rmdif, abdif, mincv,
sddif, rangedif, simlev, phidif, meandif, bestdif,
stime, maxtime)A vector. Indications of termination criteria.
Maximum iteration
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Generation number
A matrix. Best fitness of each generation
Fitness values of current generation
Global optimum value
Difference from global optimum value
k value for minimum difference of the mean of the last k best fitness values.
The minimum difference between the mean of the last k best fitness values and the best fitness value in the current generation.
Minimum difference between best fitness value and mean of fitness values
Minimum coefficient of variance
The minimum difference between the last two standard deviations.
Minimum and maximum difference (range of change)
Similarity percentage of fitness values
Phi convergence
The minimum difference between the last two fitness values
Percentage of difference between the last two best fitness values
System time saved before starting GA
Maximum running time
Termination criterion
0 : No termination
1 : Maximum iteration
2 : Reaching the global optimum value
3 : Converging the global optimum
4 : The minimum difference between the last two fitness values
5 : Percentage of difference between the last two best fitness values
6 : Minimum difference of the mean of the last k best fitness values
7 : Minimum difference between best fitness value and mean of fitness values
8 : The minimum difference between the last two standard deviations.
9 : Minimum and maximum difference (range of change)
10: Minimum coefficient of variance
11: Phi convergence
12: Similarity percentage of fitness values
13: Maximum running time