genetic-algorithm

问题 Let's say I have these two numbers: x = 0xB7 y = 0xD9 Their binary representations are: x = 1011 0111 y = 1101 1001 Now I want to crossover (GA) at a given point, say from position 4 onwards. The expected result should be: x = 1011 1001 y = 1101 0111 Bitwise, how can I achieve this? 回答1: I would just use bitwise operators: t = (x & 0x0f) x = (x & 0xf0) | (y & 0x0f) y = (y & 0xf0) | t That would work for that specific case. In order to make it more adaptable, I'd put it in a function,

问题 Let's say I have these two numbers: x = 0xB7 y = 0xD9 Their binary representations are: x = 1011 0111 y = 1101 1001 Now I want to crossover (GA) at a given point, say from position 4 onwards. The expected result should be: x = 1011 1001 y = 1101 0111 Bitwise, how can I achieve this? 回答1: I would just use bitwise operators: t = (x & 0x0f) x = (x & 0xf0) | (y & 0x0f) y = (y & 0xf0) | t That would work for that specific case. In order to make it more adaptable, I'd put it in a function,

问题 Let's say I have these two numbers: x = 0xB7 y = 0xD9 Their binary representations are: x = 1011 0111 y = 1101 1001 Now I want to crossover (GA) at a given point, say from position 4 onwards. The expected result should be: x = 1011 1001 y = 1101 0111 Bitwise, how can I achieve this? 回答1: I would just use bitwise operators: t = (x & 0x0f) x = (x & 0xf0) | (y & 0x0f) y = (y & 0xf0) | t That would work for that specific case. In order to make it more adaptable, I'd put it in a function,

问题 I'm building a model about airline scheduling by using genetic algorithms that generate a flight schedule on a daily basis and assigning the right aircraft too. Each chromosome represents a total of 50 flight legs a day(including the return trip that means 100 trips a day) and I have 42 legs, so obviously there will be repeated flight legs. The initial members are created randomly, and there are some constraints that must be satisfied to have a valid schedule. The problem is one of the

问题 I am implementing a Genetic Algorithm. For this algorithm a number of iterations (between 100 to 500) have to be done where in each iteration all 100 individuals are evaluated for their 'fitness'. To this extent, I have written an evaluate function. However, even for one iteration evaluating the fitness of the 100 individuals already takes 13 seconds. I have to speed this up massively in order to implement an efficient algorithm. The evaluate function takes two arguments, and then performs

问题 I'm new to C++ and I am trying to create a basic genetic algorithm. I created a Chromosome class and want to create a Society class that generates a vector of these Chromosomes with randomly generated "genes". Genes being the vector in the Chromosome that holds values of 0 or 1. I was testing out the Chromosome constructor, and all of the objects have the same gene vectors. How can I make the constructor generate random values? I have included code below. Any other coding practice or

问题 I'm new to C++ and I am trying to create a basic genetic algorithm. I created a Chromosome class and want to create a Society class that generates a vector of these Chromosomes with randomly generated "genes". Genes being the vector in the Chromosome that holds values of 0 or 1. I was testing out the Chromosome constructor, and all of the objects have the same gene vectors. How can I make the constructor generate random values? I have included code below. Any other coding practice or

问题 Running a GA code on spyder through Anaconda, the script runs till the end and just before running the well plotter ( see below): # Well Plotter pdf = matplotlib.backends.backend_pdf.PdfPages("ROP Log.pdf") plt.figure(figsize=(5,21)) plt.plot(well_proposal['Pred_ROP'] , well_proposal['AHD'], c='r', label= 'Predicted ROP') plt.ylim( bottom =max(well_proposal['AHD']), top =min(well_proposal['AHD'])) plt.xlim(right = 100, left = 0) plt.title('ROP VS Along Hole Depth') plt.ylabel("Along Hole

问题 Running a GA code on spyder through Anaconda, the script runs till the end and just before running the well plotter ( see below): # Well Plotter pdf = matplotlib.backends.backend_pdf.PdfPages("ROP Log.pdf") plt.figure(figsize=(5,21)) plt.plot(well_proposal['Pred_ROP'] , well_proposal['AHD'], c='r', label= 'Predicted ROP') plt.ylim( bottom =max(well_proposal['AHD']), top =min(well_proposal['AHD'])) plt.xlim(right = 100, left = 0) plt.title('ROP VS Along Hole Depth') plt.ylabel("Along Hole

问题 Warning, this is gonna be long since I want to be as specific as I can be. Exact problem: This is a multi-processing problem. I have ensured that my classes all behave as built/expected in previous experiments. edit: said threading beforehand. When I run toy example of my problem in a threaded environment, everything behaves; however, when I transition into my real problem, the code breaks. Specifically, I get a TypeError: can't pickle _thread.lock objects error. Full stack is at the bottom.