實值編碼[1]

實值編碼遺傳演算法（RCGA）的染色體空間和問題解空間是同一個空間，較好的解決了二進位制編碼遺傳演算法（BCGA）存在的求解精度和冗餘程式碼等問題。

程式碼（aimfuc）

import numpy as np


def aimfuc(Phen, LegV):
	x = Phen[:, [0]]
	f = x + 10 * np.sin(5 * x) + 7 * np.cos(4 * x)
	return [f, LegV]

程式碼（main）

import numpy as np
import geatpy as ga

AIM_M = __import__('aimfuc')
x = [0, 10]
b = [1, 1]
# codes = [1]
precisions = [6]
# scales = [0]
ranges = np.vstack([x]).T
borders = np.vstack([b]).T

fieldd = ga.crtfld(ranges, borders, precisions)  # , codes, scales)
problem = 'R'
maxormin = -1
MAXGEN = 100
NIND = 50
SUBPOP = 1
GGAP = 0.65
pm = 0.05
selectStyle = 'rws'
recombinStyle = 'xovsp'
drawing = 1

[pop_trace, var_trcae, times] = ga.sga_real_templet(AIM_M, AIM_F="aimfuc", PUN_M=None, PUN_F=None, FieldDR=fieldd,
                                                    problem=problem, maxormin=-1, MAXGEN=MAXGEN, NIND=NIND,
                                                    SUBPOP=SUBPOP, GGAP=GGAP, selectStyle=selectStyle,
                                                    recombinStyle=recombinStyle, recopt=None, pm=pm, distribute=True,
                                                    drawing=1)

 

結果

參考文獻

[1]GB/T 7714
張東民, 廖文和. 基於實值編碼遺傳演算法的起重機伸縮臂結構優化[J]. 南京航空航天大學學報, 2004, (2):185-189.