遗传算法解决TSP问题 Python实现【160行以内代码】

绝地灬酷狼 2022-04-05 13:54 341阅读 0赞

## 简述 ##

之前通过[遗传算法（Genetic Algorithm ）+C++实现解决TSP问题][Genetic Algorithm _C_TSP] 写了一些基本的原理。并且给出了C++版本代码。

相比于近300行的C++程序，Python只用了160行就解决了 可以说是非常方便了~

## 基于之前的C++版本的Python版本代码 ##

import numpy as np
    import random
    
    
    def read_data(file='data.txt'):
        with open(file, 'r') as f:
            N = int(f.readline().replace('\n', ''))
            Mat = [0] * 10
            for i in range(N):
                Mat[i] = list(map(int, f.readline().replace('\n', '').split(' ')))
        return N, Mat
    
    
    def calpathValue(path):
        global Mat
        temp = Mat[0][path[0]]
        for i in range(len(path) - 1):
            temp += Mat[path[i]][path[i + 1]]
        temp += Mat[path[-1]][0]
        return temp
    
    
    def initial():
        global N
        init = list(range(1, N, 1))
        pack = [0] * LEN
        packValue = [0] * LEN
        for i in range(LEN):
            random.shuffle(init)
            data = init
            pack[i] = data.copy()
            packValue[i] = calpathValue(pack[i])
        indexes = np.argsort(packValue)
        pack = np.array(pack)[indexes]
        packValue = np.sort(packValue)
        return packValue, pack
    
    
    # i: pack
    def preserve(i):
        global tempPack, tempPackValue, pack, packValue, tempIndex
        tempPackValue[tempIndex] = packValue[i]
        tempPack[tempIndex] = pack[i].copy()
        tempIndex += 1
    
    
    def select():
        global N, pack, tempPack, tempPackValue, tempIndex, LEN, packValue
    
        tpk = tempPack[:tempIndex]
        tpkv = tempPackValue[:tempIndex]
    
        indexes = np.argsort(tpkv)
        tpk = np.array(tpk)[indexes]
        tpkv = np.sort(tpkv)
    
        pack = tpk[:LEN]
        packValue = tpkv[:LEN]
    
    
    def crossover(i, j):
        global N, pack, tempPack, tempPackValue, tempIndex
        times = random.randint(1, N - 2)
        indexes = [0] * times
        for t in range(times):
            if t == 0:
                indexes[t] = random.randint(0, N - times - 1)
            else:
                indexes[t] = random.randint(indexes[t - 1] + 1, N - times + t - 1)
        tempPack[tempIndex] = pack[i].copy()
        pack_j_reindex = pack[j].copy()[indexes]
        count = 0
        for v in range(N - 1):
            if count >= times: break
            if tempPack[tempIndex][v] in pack_j_reindex:
                tempPack[tempIndex][v] = pack_j_reindex[count]
                count += 1
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
    
        tempIndex += 1
        tempPack[tempIndex] = pack[j].copy()
        pack_i_reindex = pack[i].copy()[indexes]
        count = 0
        for v in range(N - 1):
            if count >= times: break
            if tempPack[tempIndex][v] in pack_i_reindex:
                tempPack[tempIndex][v] = pack_i_reindex[count]
                count += 1
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
    
        tempIndex += 1
    
    
    def mutation(i):
        global N, pack, tempPack, tempPackValue, tempIndex
        times = random.randint(1, N - 2)
        indexes = [0] * times
        for t in range(times):
            if t == 0:
                indexes[t] = random.randint(0, N - times - 1)
            else:
                indexes[t] = random.randint(indexes[t - 1] + 1, N - times + t - 1)
        origin_indexes = indexes.copy()
        random.shuffle(indexes)
        tempPack[tempIndex] = pack[i].copy()
    
        for t in range(times):
            tempPack[tempIndex][indexes[t]] = pack[i][origin_indexes[t]]
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
        tempIndex += 1
    
    
    if __name__ == '__main__':
        N, Mat = read_data()
    
        LEN = 25
        pc, pm = 0.7, 0.97
        NOTMORETHANstayINGV = 10
    
        packValue, pack = initial()
    
        tempLEN = LEN * LEN
        tempPack = [[0] * N] * tempLEN
        tempPackValue = [0] * tempLEN
    
        tempIndex = 0
    
        global_Value = packValue[0]
        stayinGV = 0
    
        while True:
            tempIndex = 0
            for i in range(LEN):
                preserve(i)
                if random.random() < pm:
                    mutation(i)
                if i == LEN - 1: break
                for j in range(i + 1, LEN):
                    if tempIndex >= tempLEN: break
                    if random.random() < pc:
                        crossover(i, j)
            select()
            if packValue[0] < global_Value:
                global_Value = packValue[0]
                stayinGV = 0
            elif packValue[0] == global_Value:
                stayinGV += 1
            else:
                print("Something wrong")
                break
            if stayinGV == NOTMORETHANstayINGV:
                break
    
        print(global_Value)
        print(0, end='-->')
        for i in pack[0]:
            print(i, end='-->')

*  所用的数据：
    
     *  表示是的10个点之间的距离矩阵

10
    0 58 82 89 17 50 26 48 70 19
    58 0 74 46 70 2 70 49 87 60
    82 74 0 58 76 98 37 97 34 67
    89 46 58 0 15 17 28 69 46 79
    17 70 76 15 0 98 60 69 97 89
    50 2 98 17 98 0 81 14 43 47
    26 70 37 28 60 81 0 43 73 56
    48 49 97 69 69 14 43 0 39 0
    70 87 34 46 97 43 73 39 0 53
    19 60 67 79 89 47 56 0 53 0

### 随机生成数据并展示动图 ###

*  黑色的点是起点。
 *  我在知乎上看到类似的图，就试着改了下自己的代码也实现了这个效果。生成gif是基于我之前写的代码

![在这里插入图片描述][20181212200730860.gif]

import numpy as np
    import random
    import matplotlib.pyplot as plt
    import os
    import shutil
    import imageio
    
    def create_data(N, xu=10, yu=10, xd=-10, yd=-10):
        fx = lambda: random.random() * (xu - xd) + xd
        fy = lambda: random.random() * (yu - yd) + yd
        calDistance = lambda x, y: np.sqrt((x[0] - y[0]) ** 2 + (x[1] - y[1]) ** 2)
    
        points = [(0, 0)] * N
        for i in range(N):
            points[i] = (fx(), fy())
        Mat = np.zeros((N, N))
        for i in range(N):
            for j in range(i + 1, N):
                dv = calDistance(points[i], points[j])
                Mat[i][j], Mat[j][i] = dv, dv
        return points, Mat
    
    
    def calpathValue(path):
        global Mat
        temp = Mat[0][path[0]]
        for i in range(len(path) - 1):
            temp += Mat[path[i]][path[i + 1]]
        temp += Mat[path[-1]][0]
        return temp
    
    
    def initial():
        global N
        init = list(range(1, N, 1))
        pack = [0] * LEN
        packValue = [0] * LEN
        for i in range(LEN):
            random.shuffle(init)
            data = init
            pack[i] = data.copy()
            packValue[i] = calpathValue(pack[i])
        indexes = np.argsort(packValue)
        pack = np.array(pack)[indexes]
        packValue = np.sort(packValue)
        return packValue, pack
    
    
    # i: pack
    def preserve(i):
        global tempPack, tempPackValue, pack, packValue, tempIndex
        tempPackValue[tempIndex] = packValue[i]
        tempPack[tempIndex] = pack[i].copy()
        tempIndex += 1
    
    
    def select():
        global N, pack, tempPack, tempPackValue, tempIndex, LEN, packValue
    
        tpk = tempPack[:tempIndex]
        tpkv = tempPackValue[:tempIndex]
    
        indexes = np.argsort(tpkv)
        tpk = np.array(tpk)[indexes]
        tpkv = np.sort(tpkv)
    
        pack = tpk[:LEN]
        packValue = tpkv[:LEN]
    
    
    def crossover(i, j):
        global N, pack, tempPack, tempPackValue, tempIndex
        times = random.randint(1, N - 2)
        indexes = [0] * times
        for t in range(times):
            if t == 0:
                indexes[t] = random.randint(0, N - times - 1)
            else:
                indexes[t] = random.randint(indexes[t - 1] + 1, N - times + t - 1)
        tempPack[tempIndex] = pack[i].copy()
        pack_j_reindex = pack[j].copy()[indexes]
        count = 0
        for v in range(N - 1):
            if count >= times: break
            if tempPack[tempIndex][v] in pack_j_reindex:
                tempPack[tempIndex][v] = pack_j_reindex[count]
                count += 1
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
    
        tempIndex += 1
        tempPack[tempIndex] = pack[j].copy()
        pack_i_reindex = pack[i].copy()[indexes]
        count = 0
        for v in range(N - 1):
            if count >= times: break
            if tempPack[tempIndex][v] in pack_i_reindex:
                tempPack[tempIndex][v] = pack_i_reindex[count]
                count += 1
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
    
        tempIndex += 1
    
    
    def mutation(i):
        global N, pack, tempPack, tempPackValue, tempIndex
        times = random.randint(1, N - 2)
        indexes = [0] * times
        for t in range(times):
            if t == 0:
                indexes[t] = random.randint(0, N - times - 1)
            else:
                indexes[t] = random.randint(indexes[t - 1] + 1, N - times + t - 1)
        origin_indexes = indexes.copy()
        random.shuffle(indexes)
        tempPack[tempIndex] = pack[i].copy()
    
        for t in range(times):
            tempPack[tempIndex][indexes[t]] = pack[i][origin_indexes[t]]
        tempPackValue[tempIndex] = calpathValue(tempPack[tempIndex])
        tempIndex += 1
    
    
    def draw(path, pv):
        global points, N, TIMESIT, PNGFILE, PNGLIST
        plt.cla()
        plt.title('cross=%.4f' % pv)
        xs = [p[0] for p in points]
        ys = [p[1] for p in points]
        plt.scatter(xs, ys, color='b')
        xs = np.array(xs)
        ys = np.array(ys)
        plt.plot(xs[[0, path[0]]], ys[[0, path[0]]], color='r')
        for i in range(N - 2):
            plt.plot(xs[[path[i], path[i + 1]]], ys[[path[i], path[i + 1]]], color='r')
        plt.plot(xs[[path[N - 2], 0]], ys[[path[N - 2], 0]], color='r')
        plt.scatter(xs[0], ys[0], color='k', linewidth=10)
        plt.savefig('%s/%d.png' % (PNGFILE, TIMESIT))
        PNGLIST.append('%s/%d.png' % (PNGFILE, TIMESIT))
        TIMESIT += 1
    
    
    if __name__ == '__main__':
        # N, Mat = read_data()
        TIMESIT = 0
        PNGFILE = './png/'
        PNGLIST = []
        if not os.path.exists(PNGFILE):
            os.mkdir(PNGFILE)
        else:
            shutil.rmtree(PNGFILE)
            os.mkdir(PNGFILE)
    
        N = 20
        points, Mat = create_data(N)
        LEN = 40
        pc, pm = 0.7, 0.97
        NOTMORETHANstayINGV = 30
    
        packValue, pack = initial()
    
        tempLEN = LEN * LEN
        tempPack = [[0] * N] * tempLEN
        tempPackValue = [0] * tempLEN
    
        tempIndex = 0
    
        global_Value = packValue[0]
        draw(pack[0], global_Value)
        stayinGV = 0
    
        while True:
            tempIndex = 0
            for i in range(LEN):
                preserve(i)
                if random.random() < pm:
                    mutation(i)
                if i == LEN - 1: break
                for j in range(i + 1, LEN):
                    if tempIndex >= tempLEN: break
                    if random.random() < pc:
                        crossover(i, j)
            select()
            if packValue[0] < global_Value:
                global_Value = packValue[0]
                draw(pack[0], global_Value)
                stayinGV = 0
            elif packValue[0] == global_Value:
                stayinGV += 1
            else:
                print("Something wrong")
                break
            if stayinGV == NOTMORETHANstayINGV:
                break
    
        print(global_Value)
        print(0, end='-->')
        for i in pack[0]:
            print(i, end='-->')
    
        generated_images = []
        for png_path in PNGLIST:
            generated_images.append(imageio.imread(png_path))
        shutil.rmtree(PNGFILE)  # 可删掉
        generated_images = generated_images + [generated_images[-1]] * 5
        imageio.mimsave('TSP-GA.gif', generated_images, 'GIF', duration=0.5)

[Genetic Algorithm _C_TSP]: https://blog.csdn.net/a19990412/article/details/84900775
[20181212200730860.gif]: /images/20220405/129925081ebe455ebe6093168c6b081d.png