In a country popular for train travel, you have planned some train travelling one year in advance. The days of the year that you will travel is given as an array days
. Each day is an integer from 1
to 365
.
Train tickets are sold in 3 different ways:
- a 1-day pass is sold for
costs[0]
dollars; - a 7-day pass is sold for
costs[1]
dollars; - a 30-day pass is sold for
costs[2]
dollars.
The passes allow that many days of consecutive travel. For example, if we get a 7-day pass on day 2, then we can travel for 7 days: day 2, 3, 4, 5, 6, 7, and 8.
Return the minimum number of dollars you need to travel every day in the given list of days
.
Example 1:
Input: days = [1,4,6,7,8,20], costs = [2,7,15]
Output: 11
Explanation:
For example, here is one way to buy passes that lets you travel your travel plan:
On day 1, you bought a 1-day pass for costs[0] = $2, which covered day 1.
On day 3, you bought a 7-day pass for costs[1] = $7, which covered days 3, 4, ..., 9.
On day 20, you bought a 1-day pass for costs[0] = $2, which covered day 20.
In total you spent $11 and covered all the days of your travel.
Example 2:
Input: days = [1,2,3,4,5,6,7,8,9,10,30,31], costs = [2,7,15]
Output: 17
Explanation:
For example, here is one way to buy passes that lets you travel your travel plan:
On day 1, you bought a 30-day pass for costs[2] = $15 which covered days 1, 2, ..., 30.
On day 31, you bought a 1-day pass for costs[0] = $2 which covered day 31.
In total you spent $17 and covered all the days of your travel.
Note:
1 <= days.length <= 365
1 <= days[i] <= 365
days
is in strictly increasing order.costs.length == 3
1 <= costs[i] <= 1000
这道题给了两个数组 days 和 costs,说是有人会在指定的天数进行旅游,由于某些城市的旅游景点比较多,短时间内可能玩不完,所有有些城市会推出 city pass,就是在特定的天数内,可以随意玩。这里博主不得不提亚特兰大的 city pass,总体感觉还是蛮划算的,可以玩的很开心。现在说是有三种 city pass,一天,一周,和一个月的通玩票,价格不同,现在问应该如何去买,才能保证在给定的天数都玩到,而且花费最小。当然实际情况中,肯定是月票价格大于周票大于日票,但是这道题里并没有这个限制,cost 值之间并不存在大小关系。在实际情况中,如果需要连着几天玩,肯定是用长期票划算,但这里不一定哦,所以一定要算出各种情况。像这种每天游玩的票可以有三种不同的选择,即三种不同的状态,又是一道求极值的问题,可以说基本上动态规划 Dynamic Programming 就是不二之选。这里可以使用一个一维的 dp 数组,其中 dp[i] 表示游玩到第 days[i] 天时所需要的最小花费。接下来就是最难的部分了,找出状态转移方程。对于第 days[i] 天的花费,可能有三种不同的情况,首先是第 days[i-1] 使用了一张日票,则当前天就有多种选择,可以买日票,周票,或者月票。若之前使用买过了周票,则当前并不用再花钱了,所以只要一周内买过周票,当前就不用花钱了,但是当前的 dp 值还是需要被更新的,用买周票的前一天的 dp 值加上周票的价格来更新当前的 dp 值,所以显而易见是需要两个 for 循环的,外层的是遍历游玩天数,内层是不停的通过用买周票或者月票的方式,来查找一种最省钱的方法。具体来看代码,这里的 dp 数组大小为 n+1,为了防止减1溢出,并且都初始化为整型最大值,但是 dp[0] 要初始化为0。然后就是外层 for 循环了,i从1遍历到n,由于每一天都可以买日票,所以都可以用前一天的 dp 值加上日票价格来更新当前的 dp 值。然后就是内层循环了,j从1遍历到i,只要遍历到的某天在当前天的7天之内,就可以用尝试着替换成周票来更新当前的 dp 值,同理,若只要遍历到的某天在当前天的 30 天之内,就可以用尝试着替换成月票来更新当前的 dp 值,这样更新下来,最优解就会存到 dp 数组种的最后一个位置上了,参见代码如下:
解法一:
class Solution {
public:
int mincostTickets(vector<int>& days, vector<int>& costs) {
int n = days.size();
vector<int> dp(n + 1, INT_MAX);
dp[0] = 0;
for (int i = 1; i <= n; ++i) {
dp[i] = min(dp[i], dp[i - 1] + costs[0]);
for (int j = 1; j <= i; ++j) {
if (days[j - 1] + 7 > days[i - 1]) {
dp[i] = min(dp[i], dp[j - 1] + costs[1]);
}
if (days[j - 1] + 30 > days[i - 1]) {
dp[i] = min(dp[i], dp[j - 1] + costs[2]);
}
}
}
return dp.back();
}
};
下面来看一种更简洁的写法,由于规定了游玩的天数是在一年内,实际上可以将 dp 数组的大小确定为 366,然后只要更新好这个 dp 数组就行了。同时,由于并不是每天都要玩,所以需要知道到底是哪些天需要玩,比较简单的方法就是把游玩的天数放到一个 TreeSet 中,以便于快速的查询。用 for 循环遍历1到 365 天,用前一天的 dp 值来更新当前天,因为就算今天没有玩,之前花了的钱也都已经花了,还是要记在那,以便年底算总账。若当前天游玩了,即在 TreeSet 里面,则考虑是否可以优化当前的花费,通过三种途径,今天买日票,一周前买周票,或者一个月钱买月票,看哪种花费最低,用来更新当前的 dp 值,参见代码如下:
解法二:
class Solution {
public:
int mincostTickets(vector<int>& days, vector<int>& costs) {
unordered_set<int> st(days.begin(), days.end());
vector<int> dp(366);
for (int i = 1; i <= 365; ++i) {
dp[i] = dp[i - 1];
if (st.count(i)) {
dp[i] = min({dp[i - 1] + costs[0], dp[max(0, i - 7)] + costs[1], dp[max(0, i - 30)] + costs[2]});
}
}
return dp.back();
}
};
Github 同步地址:
https://github.com/grandyang/leetcode/issues/983
类似题目:
参考资料:
https://leetcode.com/problems/minimum-cost-for-tickets/
https://leetcode.com/problems/minimum-cost-for-tickets/discuss/226659/Two-DP-solutions-with-pictures
LeetCode All in One 题目讲解汇总(持续更新中…)
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