def run3(problem):
ga = GA.GA_BASIC(problem)
start = time.process_time()
ga.run()
end = time.process_time()
run_time = end - start
print("********* GA_BASIC runtime: *********")
print(run_time)
y1 = ga.memo_opt[0:-1]
x1 = np.arange(1, len(y1) + 1)
l1 = plt.plot(x1, y1, 'r--', label='GA_BASIC')
plt.plot(x1, y1, 'r-')
plt.title('The Convergence Curve of GA')
plt.xlabel('Iteration')
plt.ylabel('Best Objective')
plt.legend()
plt.show()
print("**************** GA_BASIC ****************")
print([a for a in ga.opt_chromo])
print("********* GA_BASIC Block lasts: *********")
for i in ga.memo_FV[tuple(ga.opt_chromo)].block_lasts:
print(i)
print("********* GA_BASIC end times: *********")
for i in ga.memo_FV[tuple(ga.opt_chromo)].end_times:
print(i)
print("********* GA_BASEIC eti_penalty: *********")
print("overall penalty of GA_BASIC:",
ga.memo_FV[tuple(ga.opt_chromo)].eti_penalty)
def run5(p):
ga_basic = GA.GA_BASIC(p)
start = time.process_time()
ga_basic.run()
end = time.process_time()
run_time = end - start
b_ratio = ga_basic.memo_FV[tuple(ga_basic.opt_chromo)].b_ratio
f = open('basicGA_results.txt', 'a')
f.write(
str(p.n) + "\t" + str(p.b) + "\t" + str(p.rho) + "\t" + str(run_time) +
"\t" + str(b_ratio) + "\n")
f.close()
def run5(p):
ga = GA.GA_BASIC(p)
start = time.process_time()
ga.run()
end = time.process_time()
run_time = end - start
f = open('GA_My_DP_0717.txt', 'a')
f.write(
str(p.n) + "\t" + str(p.b) + "\t" + str(p.rho) + "\t" + str(run_time) +
"\t" + str(ga.memo_opt[ga.max_iter]) + "\t" +
str(ga.memo_opt[ga.max_iter - 5]) + "\t" +
str(ga.memo_opt[ga.max_iter - 10]) + "\n")
f.close()