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()