# Posts tagged as “greedy”

You are given a string num, representing a large integer, and an integer k.

We call some integer wonderful if it is a permutation of the digits in num and is greater in value than num. There can be many wonderful integers. However, we only care about the smallest-valued ones.

• For example, when num = "5489355142":
• The 1st smallest wonderful integer is "5489355214".
• The 2nd smallest wonderful integer is "5489355241".
• The 3rd smallest wonderful integer is "5489355412".
• The 4th smallest wonderful integer is "5489355421".

Return the minimum number of adjacent digit swaps that needs to be applied to num to reach the kth smallest wonderful integer.

The tests are generated in such a way that kth smallest wonderful integer exists.

Example 1:

Input: num = "5489355142", k = 4
Output: 2
Explanation: The 4th smallest wonderful number is "5489355421". To get this number:
- Swap index 7 with index 8: "5489355142" -> "5489355412"
- Swap index 8 with index 9: "5489355412" -> "5489355421"


Example 2:

Input: num = "11112", k = 4
Output: 4
Explanation: The 4th smallest wonderful number is "21111". To get this number:
- Swap index 3 with index 4: "11112" -> "11121"
- Swap index 2 with index 3: "11121" -> "11211"
- Swap index 1 with index 2: "11211" -> "12111"
- Swap index 0 with index 1: "12111" -> "21111"


Example 3:

Input: num = "00123", k = 1
Output: 1
Explanation: The 1st smallest wonderful number is "00132". To get this number:
- Swap index 3 with index 4: "00123" -> "00132"


Constraints:

• 2 <= num.length <= 1000
• 1 <= k <= 1000
• num only consists of digits.

## Solution: Next Permutation + Greedy

Time complexity: O(k*n + n^2)
Space complexity: O(n)

## C++

It is a sweltering summer day, and a boy wants to buy some ice cream bars.

At the store, there are n ice cream bars. You are given an array costs of length n, where costs[i] is the price of the ith ice cream bar in coins. The boy initially has coins coins to spend, and he wants to buy as many ice cream bars as possible.

Return the maximum number of ice cream bars the boy can buy with coins coins.

Note: The boy can buy the ice cream bars in any order.

Example 1:

Input: costs = [1,3,2,4,1], coins = 7
Output: 4
Explanation: The boy can buy ice cream bars at indices 0,1,2,4 for a total price of 1 + 3 + 2 + 1 = 7.


Example 2:

Input: costs = [10,6,8,7,7,8], coins = 5
Output: 0
Explanation: The boy cannot afford any of the ice cream bars.


Example 3:

Input: costs = [1,6,3,1,2,5], coins = 20
Output: 6
Explanation: The boy can buy all the ice cream bars for a total price of 1 + 6 + 3 + 1 + 2 + 5 = 18.


Constraints:

• costs.length == n
• 1 <= n <= 105
• 1 <= costs[i] <= 105
• 1 <= coins <= 108

## Solution: Greedy

Sort by price in ascending order, buy from the lowest price to the highest price.

Time complexity: O(nlogn)
Space complexity: O(1)

## C++

You are given three positive integers nindex and maxSum. You want to construct an array nums (0-indexed) that satisfies the following conditions:

• nums.length == n
• nums[i] is a positive integer where 0 <= i < n.
• abs(nums[i] - nums[i+1]) <= 1 where 0 <= i < n-1.
• The sum of all the elements of nums does not exceed maxSum.
• nums[index] is maximized.

Return nums[index] of the constructed array.

Note that abs(x) equals x if x >= 0, and -x otherwise.

Example 1:

Input: n = 4, index = 2,  maxSum = 6
Output: 2
Explanation: The arrays [1,1,2,1] and [1,2,2,1] satisfy all the conditions. There are no other valid arrays with a larger value at the given index.


Example 2:

Input: n = 6, index = 1,  maxSum = 10
Output: 3


Constraints:

• 1 <= n <= maxSum <= 109
• 0 <= index < n

## Solution: Binary Search

To maximize nums[index], we can construct an array like this:
[1, 1, 1, …, 1, 2, 3, …, k – 1, k, k – 1, …,3, 2, 1, …., 1, 1, 1]

Time complexity: O(logn)
Space complexity: O(1)

## C++

You are given an integer array coins of length n which represents the n coins that you own. The value of the ith coin is coins[i]. You can make some value x if you can choose some of your n coins such that their values sum up to x.

Return the maximum number of consecutive integer values that you can make with your coins starting from and including 0.

Note that you may have multiple coins of the same value.

Example 1:

Input: coins = [1,3]
Output: 2
Explanation: You can make the following values:
- 0: take []
- 1: take 
You can make 2 consecutive integer values starting from 0.

Example 2:

Input: coins = [1,1,1,4]
Output: 8
Explanation: You can make the following values:
- 0: take []
- 1: take 
- 2: take [1,1]
- 3: take [1,1,1]
- 4: take 
- 5: take [4,1]
- 6: take [4,1,1]
- 7: take [4,1,1,1]
You can make 8 consecutive integer values starting from 0.

Example 3:

Input: nums = [1,4,10,3,1]
Output: 20

Constraints:

• coins.length == n
• 1 <= n <= 4 * 104
• 1 <= coins[i] <= 4 * 104

## Solution: Greedy + Math

We want to start with smaller values, sort input array in ascending order.

First of all, the first number has to be 1 in order to generate sum of 1.
Assuming the first i numbers can generate 0 ~ k.
Then the i+1-th number x can be used if and only if x <= k + 1, such that we can have a consecutive sum of k + 1 by adding x to a sum between [0, k] and the new maximum sum we have will be k + x.

Time complexity: O(nlogn)
Space complexity: O(1)

## C++

You are given an array of integers nums (0-indexed) and an integer k.

The score of a subarray (i, j) is defined as min(nums[i], nums[i+1], ..., nums[j]) * (j - i + 1). A good subarray is a subarray where i <= k <= j.

Return the maximum possible score of a good subarray.

Example 1:

Input: nums = [1,4,3,7,4,5], k = 3
Output: 15
Explanation: The optimal subarray is (1, 5) with a score of min(4,3,7,4,5) * (5-1+1) = 3 * 5 = 15.


Example 2:

Input: nums = [5,5,4,5,4,1,1,1], k = 0
Output: 20
Explanation: The optimal subarray is (0, 4) with a score of min(5,5,4,5,4) * (4-0+1) = 4 * 5 = 20.


Constraints:

• 1 <= nums.length <= 105
• 1 <= nums[i] <= 2 * 104
• 0 <= k < nums.length

## Solutions: Two Pointers

maintain a window [i, j], m = min(nums[i~j]), expend to the left if nums[i – 1] >= nums[j + 1], otherwise expend to the right.

Time complexity: O(n)
Space complexity: O(1)