动态规划:小偷的背包
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《算法图解》第九章,小偷的背包问题,顺便记录一下:
import copy def fillbag(bagsize, goods): bagsvalue = [[{}]*bagsize for x in range(len(goods))] def bestbag( m, n, leftweight, value, name): ‘‘‘ m, 行号,同时表示 m 种物品 n, 列, 同时表示当前背包大小 leftweight, 剩余空间, value, 当前物品价值 name, 当前物品 ‘‘‘ # 注意: # 使用 m_sub1, 说明问题域为 m-1 种物品(排除当前物品,说明每种物品只有一个,不可重复) # 背包大小为 leftweight m_sub1 = m-1 a = bagsvalue[m_sub1][n]["v"] b = value if leftweight != 0: b += bagsvalue[m_sub1][leftweight-1]["v"] if a > b: return copy.deepcopy(bagsvalue[m_sub1][n]) else: if leftweight == 0: return {"v":v,"gs":[name]} else: bag = copy.deepcopy(bagsvalue[m_sub1][leftweight-1]) bag["v"]=b bag["gs"].append(name) return bag for i in range(len(goods)): na = goods[i]["name"] w = goods[i]["weight"] v = goods[i]["value"] for j in range(bagsize): # 背包当前大小 cw = j+1 if i == 0: if w <= (j+1): bagsvalue[i][j] = {"v":v,"gs":[na]} else: bagsvalue[i][j] = {"v":0,"gs":[]} continue # 剩余空间 lw = cw - w if cw < w: bagsvalue[i][j] = copy.deepcopy(bagsvalue[i-1][j]) else: bagsvalue[i][j] = bestbag(i,j,lw,v,na) return bagsvalue def main(): bagsize = 4; goods = [{"name":"soundbox","weight":4,"value":3000}, {"name":"guitar","weight":1,"value":1500}, {"name":"laptop","weight":2,"value":2000}, {"name":"iphone","weight":1,"value":2000}] bagvalues = fillbag(4,goods) print(bagvalues) if __name__ == "__main__": main()
如果是同一种物品数量不限,肯定是按照单位价值的高低朝包里收拾啦。
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