Rod cutting problem

Dynamic Programming DP on subsequences Hard
  • This algorithm, also known as Rod Cutting Problem, is a classic example of Dynamic Programming
  • It's a practical real-world issue utilized in industries like manufacturing and construction, where the efficient use of resources is crucial
  • For example, it could be used in a steel plant to determine the best way to cut steel rods to minimize waste while maximizing profit
  • Similarly, in software development, it is used in resource allocation problems, optimizing network routing, or even in managing cloud resources to lower costs by optimizing the way the resources are used

Given a rod of length N inches and an array price[] where price[i] denotes the value of a piece of rod of length i inches (1-based indexing). Determine the maximum value obtainable by cutting up the rod and selling the pieces. Make any number of cuts, or none at all, and sell the resulting pieces.

Examples:

Input: price = [1, 6, 8, 9, 10, 19, 7, 20], N = 8

Output: 25

Explanation: Cut the rod into lengths of 2 and 6 for a total price of 6 + 19= 25.

Input: price = [1, 5, 8, 9], N = 4

Output: 10

Explanation: Cut the rod into lengths of 2 and 2 for a total price of 5 + 5 = 10.

Input: price = [5, 5, 8, 9, 10, 17, 17, 20], N = 8

Constraints

  • 1 ≤ N ≤ 1000
  • 1 ≤ price[i] ≤ 105

Hints

  • Define dp[i] as the maximum profit obtainable for a rod of length i. the recurrence relation is:dp[i]=max(dp[i],dp[i−j]+price[j−1])
  • Instead of a full 2D DP table, we use a 1D DP array (dp[N]).

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