Python3 回朔法解決作業分配問題 （剪枝優化）

本文是在上次的基礎上做的優化，解決了窮舉結果的尷尬

文章鏈接：Python3 回朔法解決作業分配問題（http://blog.csdn.net/liangxun0712/article/details/70598467）

廢話不多說，直接上優化後的代碼

class Worker:
    max = 0  # 上界 通過貪心算法找出近似值
    min = 0  # 下界 由每組的最小值組成
    pt_nodes = []  # 存放可擴展的節點
    input_file = ''  # 輸入文件名
    output_file = ''  # 輸出文件名
    matrix = []  # 存放數據矩陣  行爲單個任務 每個工人 完成所要的時間
    n = 0  # 數據矩陣的大小 n*n
    min_cost = 10000
    worker_mark = []  # 標記工人是否被分配了任務

    #  初始化參數
    def __init__(self, input_file, output_file):
        self.input_file = input_file
        self.output_file = output_file
        self.read_data_from_file()
        self.n = len(self.matrix)
        self.get_low_limit()
        self.get_up_limit()

        print(self.matrix)
        print(self.n)
        print(self.max)
        print(self.min)

    #  從文件中讀取數據 初始化數據矩陣
    def read_data_from_file(self):
        with open(self.input_file) as source:
            for line in source:
                data_cluster = line.split(',')
                temp = []
                for value in data_cluster:
                    temp.append(int(value))
                self.matrix.append(temp)

    #  獲取數據下界  最小值之和
    def get_low_limit(self):
        for i in range(self.n):
            self.min += min(self.matrix[i])

    #  獲取數據上界  貪心算法
    def get_up_limit(self):
        #  初始化工人使用標記
        worker_mark = []
        for i in range(self.n):
            worker_mark.append(0)
        # 貪心算法 取得 近似最優解
        for i in range(self.n):
            temp = self.matrix[i]
            min_value = 5000
            index = 0
            for k in range(self.n):
                if worker_mark[k] == 0 and min_value > temp[k]:
                    min_value = temp[k]
                    index = k
            worker_mark[index] = 1  # 標記工人是否被分配
            self.max += min_value  # 累積上限值

    #  初始化工人分配標記
    def init_worker(self):
        self.worker_mark = []
        for i in range(self.n):
            self.worker_mark.append(0)

    #  剪枝優化後的回朔算法
    def branch_limit(self, deep, total):
        if deep == self.n:
            # print('最短距離', total)
            if self.min_cost > total:
                self.min_cost = total
            return
        temp = self.matrix[deep]
        for i in range(self.n):
            if self.worker_mark[i] == 0:
                if (temp[i] + total) > self.max:  # 超出上界的節點直接捨棄
                    continue
                else:
                    self.worker_mark[i] = 1
                    self.branch_limit(deep+1, total+temp[i])
                    self.worker_mark[i] = 0


input_file = 'input_assign05_01.dat'
# input_file = 'input_assign05_02.dat'
# input_file = 'input_assign05_03.dat'
output_file = 'output_01.dat'
# output_file = 'output_02.dat'
# output_file = 'output_03.dat'

worker = Worker(input_file, output_file)
worker.init_worker()
worker.branch_limit(0, 0)
print(worker.min_cost)