When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you-When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but　an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you