Introduction

In this blog post, we will explore how to solve the LeetCode problem "1011" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

A conveyor belt has packages that must be shipped from one port to another within days days. The ith package on the conveyor belt has a weight of weights[i]. Each day, we load the ship with packages on the conveyor belt (in the order given by weights). We may not load more weight than the maximum weight capacity of the ship. Return the least weight capacity of the ship that will result in all the packages on the conveyor belt being shipped within days days. Example 1: Input: weights = [1,2,3,4,5,6,7,8,9,10], days = 5 Output: 15 Explanation: A ship capacity of 15 is the minimum to ship all the packages in 5 days like this: 1st day: 1, 2, 3, 4, 5 2nd day: 6, 7 3rd day: 8 4th day: 9 5th day: 10 Note that the cargo must be shipped in the order given, so using a ship of capacity 14 and splitting the packages into parts like (2, 3, 4, 5), (1, 6, 7), (8), (9), (10) is not allowed. Example 2: Input: weights = [3,2,2,4,1,4], days = 3 Output: 6 Explanation: A ship capacity of 6 is the minimum to ship all the packages in 3 days like this: 1st day: 3, 2 2nd day: 2, 4 3rd day: 1, 4 Example 3: Input: weights = [1,2,3,1,1], days = 4 Output: 3 Explanation: 1st day: 1 2nd day: 2 3rd day: 3 4th day: 1, 1 Constraints: 1 <= days <= weights.length <= 5 * 104 1 <= weights[i] <= 500

Explanation

Here's the breakdown of the solution:

• Binary Search: The core idea is to use binary search to find the minimum capacity. The search space is bounded by the maximum weight (minimum possible capacity) and the sum of all weights (maximum possible capacity).
• Feasibility Check: For a given capacity, we check if it's feasible to ship all packages within the given number of days. We simulate the shipping process and count the number of days required.

• Adjusting Search Space: Based on the feasibility check, we adjust the binary search space. If the capacity is too low (requires more than days days), we increase the lower bound. If the capacity is sufficient (requires days or fewer days), we decrease the upper bound to search for an even smaller capacity.

• Runtime Complexity: O(N * log(Sum of weights)), where N is the number of weights.

• Storage Complexity: O(1)

Code

    def ship_within_days(weights, days):
    """
    Finds the least weight capacity of the ship that will result in all the packages on the conveyor belt being shipped within days days.

    Args:
        weights: A list of integers representing the weights of the packages.
        days: An integer representing the number of days to ship the packages.

    Returns:
        An integer representing the least weight capacity of the ship.
    """

    left = max(weights)
    right = sum(weights)

    while left < right:
        mid = (left + right) // 2
        required_days = 1
        current_weight = 0

        for weight in weights:
            if current_weight + weight <= mid:
                current_weight += weight
            else:
                required_days += 1
                current_weight = weight

        if required_days <= days:
            right = mid
        else:
            left = mid + 1

    return left