# -*- coding: utf-8 -*-
import sys
sys.setrecursionlimit(10**9)
input = sys.stdin.readline
# python template for atcoder1


def manhattan(item1, item2):

    dist = abs(item1[0]-item2[0])+abs(item1[1]-item2[1])
    #print("dist->", dist)
    return dist


def calcCost(dropItem, last_visit, weight_sum):
    dist = manhattan(dropItem, last_visit)
    cost = (weight_sum+100)/120*dist
    ret = cost+dropItem[2]
    #print("ret->", ret)
    return ret


SX, SY = map(int, input().split())
N = int(input())
items = [list(map(float, input().split())) for _ in range(N)]

dp = [[float('inf')]*N for _ in range(1 << N)]

dp[0][0] = 0
for i in range(1):
    dp[0][i] = 0

for mask in range(1 << N):
    for new_item in range(N):
        if mask >> new_item & 1:
            continue

        new_state = mask | 1 << new_item
        if mask == 0:
            weight_sum = 0
            for loaded in range(N):
                if mask >> loaded & 1 == 0:
                    weight_sum += items[loaded][2]
            cost = calcCost(items[new_item], [SX, SY], weight_sum)
            dp[new_state][new_item] = cost
        else:
            for last_visit in range(N):
                if mask >> last_visit & 1:
                    weight_sum = 0
                    for loaded in range(N):
                        if mask >> loaded & 1 == 0:
                            weight_sum += items[loaded][2]

                    cost = calcCost(items[new_item],
                                    items[last_visit], weight_sum)
                    dp[new_state][new_item] = min(
                        dp[new_state][new_item], dp[mask][last_visit]+cost)

ans = float('inf')
for i in range(N):
    ans = min(ans, dp[-1][i]+manhattan([SX, SY], items[i])*100/120)
print(ans)